# Sference AI visibility in LLM Inference & Serverless GPU

Canonical: https://devtune.ai/verticals/llm-inference-serverless-gpu/sference

[Website](https://sference.com/)

Latest AI responses: 2026-11-02
Prompts: 25
Runs: 5


## Platforms

- bing-copilot-search
- google-ai-mode
- chatgpt-search
- perplexity
- google-ai

Rank: 10
Total brands: 10
Measured responses: 125
Presence percent: 0
Share of voice percent: 0
Average position: Not available
Docs presence percent: 0
Blog presence percent: 0
Brand mention percent: 0


## Profile

Overview: Sference is an early-access async AI inference platform built for regulated EU industries. It aggregates excess and preemptible GPU capacity across multiple EU providers into a federated compute pool, enabling batch workloads to run at up to 75% below real-time inference costs by trading latency for savings. Two delivery windows are offered — Priority (~1 hour) and Overnight (~24 hours) — alongside support for open-weight models from the Qwen, Mistral, and Llama families and bring-your-own fine-tuned models compatible with vLLM or SGLang. An OpenAI-compatible batch API and CLI tool ease integration. Sference's core differentiation is combining spot-GPU economics with EU data sovereignty, full compliance audit trails, DORA and EU AI Act readiness, and BYOM — targeting SaaS companies in FinTech, LegalTech, HealthTech, and InsureTech whose customers require regulatory auditability.
Product summary: Sference is an async batch AI inference service running on federated EU spot and preemptible GPU capacity. It delivers up to 75% cost savings versus real-time inference by accepting configurable latency trade-offs, and combines EU data sovereignty, an OpenAI-compatible batch API, BYOM for fine-tuned models, and a compliance runtime (audit trails, DPA, DORA/AI Act readiness) in a single platform aimed at regulated EU SaaS verticals.


### Key capabilities

- Async batch AI inference on federated EU spot and preemptible GPU capacity
- Delivery windows: Priority (~1 hr, up to 50% off) and Overnight (~24 hr, up to 75% off)
- Bring-your-own-model (BYOM): upload fine-tuned weights, loaded per job and released after completion
- OpenAI-compatible batch API with JSONL-based CLI submission tool
- Hardware-agnostic GPU federation across multiple EU providers with no single-vendor dependency
- Fault-tolerant batch orchestration with checkpoint resumption on spot-instance preemption
- EU data residency: all requests processed on EU GPUs, zero US CLOUD Act exposure
- Compliance runtime: full request audit trail, configurable retention, exportable reports, DPA included
- DORA enforcement readiness and EU AI Act (August 2026 deployer obligations) readiness built in
- On-demand model loading per batch job — no persistent GPU memory reservation required



### Target users

- EU SaaS companies serving regulated-industry customers (FinTech, LegalTech, HealthTech, InsureTech)
- AI/ML teams running large-scale model evaluations, synthetic data generation, or fine-tuning data prep on sensitive datasets
- Document processing teams handling invoices, contracts, and forms at scale
- Engineering and compliance teams at companies subject to DORA or EU AI Act deployer obligations



### Key use cases

- Batch KYC extraction and transaction classification for FinTech compliance pipelines
- Contract corpus analysis and document review for LegalTech
- Medical record digitization and clinical data extraction for HealthTech
- Insurance claims processing and underwriting document analysis
- Large-scale model evaluations and synthetic data generation for AI/ML teams
- Fine-tuning dataset preparation on sensitive or proprietary data
- Invoice, contract, and form processing at scale for document-heavy workflows
- Embedding generation for legal and regulated-domain RAG systems

Integrations ecosystem: OpenAI-compatible batch API enabling drop-in replacement for existing batch pipelines. Backend inference runtime via vLLM and SGLang. CLI tool (`sference batch`) for submitting JSONL workloads with model and window parameters. BYOM: upload fine-tuned weights in any format compatible with vLLM/SGLang; weights are loaded per job and released after completion. No third-party marketplace listings, webhook integrations, or partner ecosystem pages are publicly confirmed.
Pricing summary: Three tiers billed per token consumed; no credit card required and no minimum spend. Dev Mode: real-time delivery at full price, intended for prompt iteration and testing. Priority: ~1-hour delivery at up to 50% off real-time rates. Overnight: ~24-hour delivery at up to 75% off real-time rates. Specific per-token rates are not published on the website.
Review summary: No third-party reviews are available. Sference is in early access and has no presence on G2, Gartner Peer Insights, or other public software review platforms as of the research date.
Competitive positioning: Sference targets the intersection of async batch AI inference, EU data sovereignty, and regulatory compliance — a combination it claims no single competitor offers in full. While US-based platforms such as Together AI and Modal Labs provide batch APIs or spot-GPU economics, Sference differentiates on three axes: (1) federated EU-only GPU infrastructure eliminating US CLOUD Act exposure; (2) bring-your-own-model (BYOM) support for fine-tuned weights with the same compliance guarantees as catalog models; and (3) compliance tooling — full audit trail, exportable reports, DPA, DORA and EU AI Act readiness — built into the runtime rather than added post-hoc. It positions as purpose-built for regulated EU SaaS verticals (FinTech, LegalTech, HealthTech, InsureTech) rather than as a general-purpose inference platform.
Limitations: Not suitable for real-time or low-latency applications (chat interfaces, live agents, interactive products). EU-only infrastructure limits global deployment options. Pre-launch / early access status means no production track record, published SLAs, or independent performance benchmarks are available. Per-token pricing rates are not disclosed on the website. Model catalog limited to open-weight Qwen, Mistral, and Llama families plus BYOM; closed-model APIs (e.g. GPT-4o) are not supported. Spot and preemptible capacity means scheduling is non-deterministic within stated delivery windows.


### Source urls

- https://sference.com/
- https://www.linkedin.com/in/jernejstrasner/
- https://www.linkedin.com/company/sference/

Research approved: 2026-05-06T17:53:53.622+00:00


### Customer outcomes





### Reviews breakdown





### Review themes



#### Praised





#### Criticized






### Company facts

Founded year: Not available
Hq: EU


#### Founders

- Jernej Strasner
- Aleksander Pejcic
- Benjamin Dobnikar

Employees range: Not available
Total funding: Not available
Valuation: Not available
Arr: Not available
Customer count: Not available
Status: Private (Early Access)


Readiness: Not available


## Ranking

| Display name | Pair count | Total pairs | Presence percent | Avg position |
| --- | --- | --- | --- | --- |
| Modal | 33 | 125 | 26.400000000000002 | 8.275862068965518 |
| RunPod | 27 | 125 | 21.6 | 5.349206349206349 |
| Baseten | 20 | 125 | 16 | 6.243243243243243 |
| Together AI | 16 | 125 | 12.8 | 5.375 |
| Fireworks AI | 12 | 125 | 9.6 | 4.84 |
| Cerebrium | 10 | 125 | 8 | 5.2105263157894735 |
| Replicate | 10 | 125 | 8 | 12.761904761904763 |
| Beam | 6 | 125 | 4.8 | 11.181818181818182 |
| Lepton AI | 0 | 125 | 0 | Not available |
| Sference | 0 | 125 | 0 | Not available |



## Platform breakdown

| Platform | Prompt count | Presence rate |
| --- | --- | --- |
| bing-copilot-search | 0 | 0 |
| google-ai-mode | 0 | 0 |
| chatgpt-search | 0 | 0 |
| perplexity | 0 | 0 |
| google-ai | 0 | 0 |



## Strengths





## Gaps

| Prompt text | Competitor presence count |
| --- | --- |
| What serverless GPU inference providers work best alongside AI orchestration frameworks so teams can chain model calls and tool use cleanly? | 5 |
| Which serverless GPU inference platforms have the best developer experience for iterating quickly on prompt templates and sampling parameters without redeploying? | 5 |
| Which serverless GPU platforms support batch inference jobs for offline processing pipelines in addition to real-time API endpoints? | 5 |
| Which serverless inference platforms support running large multimodal models — handling both text and image inputs — on high-end GPUs at production scale? | 4 |
| Which serverless GPU platforms support webhook callbacks or event-driven triggers for async inference jobs in a data pipeline built on a workflow orchestrator? | 4 |



## Topic scores

| Topic name | Prompt count | Cited prompt count |
| --- | --- | --- |
| Capability | 5 | 0 |
| Developer Experience | 5 | 0 |
| Integrations & Ecosystem | 5 | 0 |
| Performance & Reliability | 5 | 0 |
| Setup & First Run | 5 | 0 |



## Prompt results

- Prompt text: Which LLM inference platforms let enterprise teams bring their own fine-tuned model weights and enforce strict data isolation with private deployments?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Fireworks AI | 3 |
| Together AI | 6 |
| Modal | 10 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Baseten | 2 |



##### Google-ai




- Prompt text: Which LLM inference platforms support deploying quantized open-source models with minimal setup for a backend engineer with no MLOps background?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Together AI | 3 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Modal | 7 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Fireworks AI | 1 |
| RunPod | 4 |



##### Google-ai




- Prompt text: Which serverless inference platforms support running large multimodal models — handling both text and image inputs — on high-end GPUs at production scale?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 1 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 6 |
| Baseten | 7 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Modal | 1 |
| Cerebrium | 5 |
| Fireworks AI | 8 |
| Together AI | 10 |
| Replicate | 14 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 5 |



##### Google-ai




- Prompt text: Which serverless GPU platforms give engineering teams the most visibility into per-request latency and token throughput right out of the box?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Baseten | 1 |



##### Chatgpt-search





##### Perplexity

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| RunPod | 3 |



##### Google-ai




- Prompt text: Which LLM inference platforms integrate natively with vector database services for building retrieval-augmented generation pipelines without extra glue code?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode





##### Chatgpt-search





##### Perplexity





##### Google-ai




- Prompt text: Which serverless inference providers deliver the highest tokens-per-second throughput for a high-volume API serving thousands of concurrent users?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Cerebrium | 7 |



##### Chatgpt-search





##### Perplexity





##### Google-ai




- Prompt text: I'm evaluating serverless inference platforms for a small startup — which ones let you deploy a custom open-source LLM without writing any infrastructure config?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Fireworks AI | 2 |
| Together AI | 3 |
| Baseten | 4 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Baseten | 2 |
| Replicate | 3 |
| Modal | 4 |
| RunPod | 6 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Replicate | 3 |



##### Google-ai




- Prompt text: What LLM inference platforms offer the best SDK and API ergonomics for a Python-first engineering team shipping a conversational AI feature?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode





##### Chatgpt-search





##### Perplexity

| Display name | Position |
| --- | --- |
| Together AI | 4 |
| Fireworks AI | 6 |



##### Google-ai




- Prompt text: What are the most reliable LLM serving platforms for an enterprise use case that requires 99.9% uptime SLAs and geo-redundant deployments?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Fireworks AI | 7 |



##### Perplexity





##### Google-ai




- Prompt text: What LLM inference platforms can handle sudden traffic spikes — say 10x burst load — without throttling for a mid-sized SaaS product?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Together AI | 1 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Together AI | 1 |
| Baseten | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Together AI | 7 |



##### Google-ai




- Prompt text: Which serverless inference platforms make it easiest to manage multiple open-source model versions in parallel across staging and production environments?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Replicate | 4 |
| Together AI | 8 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Modal | 7 |
| Replicate | 9 |
| RunPod | 11 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Baseten | 1 |



##### Google-ai




- Prompt text: What serverless GPU inference providers work best alongside AI orchestration frameworks so teams can chain model calls and tool use cleanly?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 3 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Modal | 2 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 3 |
| Baseten | 4 |
| Fireworks AI | 5 |
| Together AI | 8 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Together AI | 2 |
| Fireworks AI | 4 |



##### Google-ai

| Display name | Position |
| --- | --- |
| Modal | 2 |
| RunPod | 4 |
| Cerebrium | 6 |


- Prompt text: Which serverless GPU inference platforms have the best developer experience for iterating quickly on prompt templates and sampling parameters without redeploying?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 1 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Together AI | 2 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 2 |
| Replicate | 3 |
| Baseten | 4 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |



##### Google-ai

| Display name | Position |
| --- | --- |
| Modal | 1 |


- Prompt text: Which serverless GPU platforms support batch inference jobs for offline processing pipelines in addition to real-time API endpoints?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Beam | 1 |
| Modal | 2 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 1 |
| Cerebrium | 5 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 2 |
| Beam | 3 |
| Cerebrium | 4 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 3 |



##### Google-ai

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 7 |


- Prompt text: Which inference platforms expose an API compatible with the standard chat completions format so switching providers requires minimal code changes?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode





##### Chatgpt-search





##### Perplexity





##### Google-ai




- Prompt text: What LLM inference platforms integrate with cloud object storage for loading large model weights at deploy time without manual upload steps?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 1 |
| Baseten | 2 |
| Cerebrium | 3 |



##### Chatgpt-search





##### Perplexity

| Display name | Position |
| --- | --- |
| Baseten | 1 |



##### Google-ai




- Prompt text: What are the fastest serverless GPU inference platforms to go from an open-source LLM to a live production API endpoint with no GPU infrastructure to manage?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 1 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 11 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Modal | 1 |
| Baseten | 2 |
| Replicate | 6 |
| Together AI | 7 |
| Fireworks AI | 9 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 4 |
| Modal | 7 |



##### Google-ai




- Prompt text: Which serverless GPU platforms support webhook callbacks or event-driven triggers for async inference jobs in a data pipeline built on a workflow orchestrator?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| RunPod | 2 |
| Replicate | 4 |
| Modal | 5 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Replicate | 2 |
| Modal | 15 |
| Baseten | 31 |
| Beam | 33 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |



##### Google-ai

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 2 |


- Prompt text: What LLM inference platforms handle streaming token responses well and support long context windows for document-processing use cases?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Fireworks AI | 1 |
| Together AI | 5 |



##### Chatgpt-search





##### Perplexity





##### Google-ai




- Prompt text: Which serverless GPU platforms have the best cost-per-token at scale for a startup burning significant GPU budget on a document summarization product?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| RunPod | 1 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Together AI | 2 |
| Fireworks AI | 3 |
| Modal | 4 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Cerebrium | 3 |
| Fireworks AI | 5 |



##### Google-ai




- Prompt text: Which LLM inference platforms have the easiest onboarding for a solo developer deploying a fine-tuned open-source model for the first time?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Together AI | 1 |



##### Chatgpt-search





##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 3 |
| Modal | 5 |



##### Google-ai




- Prompt text: What's the quickest serverless GPU platform to get an image-generation model behind a REST API with autoscaling out of the box?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 3 |



##### Google-ai-mode





##### Chatgpt-search





##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Replicate | 5 |



##### Google-ai

| Display name | Position |
| --- | --- |
| RunPod | 4 |


- Prompt text: What are the best LLM serving platforms for a small ML team that needs built-in request logging and usage dashboards without wiring up a separate observability stack?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Modal | 3 |



##### Perplexity





##### Google-ai




- Prompt text: I'm looking for an inference platform that supports custom CUDA kernels and speculative decoding — what are my options for a performance-critical chatbot?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode





##### Chatgpt-search





##### Perplexity





##### Google-ai




- Prompt text: Which serverless GPU inference platforms have the lowest cold-start latency for a customer-facing chat app that needs sub-second first-token response times?


#### Brand position by platform

Bing-copilot-search: Not available
Google-ai-mode: Not available
Chatgpt-search: Not available
Perplexity: Not available
Google-ai: Not available



#### Platform rows



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Cerebrium | 1 |
| Beam | 2 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Beam | 1 |
| Cerebrium | 2 |
| RunPod | 9 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 3 |
| Beam | 6 |
| Cerebrium | 7 |



##### Google-ai







## Top sources





## Response excerpts





## Competitor excerpts

| Platform | Competitor name | Excerpt |
| --- | --- | --- |
| bing-copilot-search | Modal | Best serverless GPU inference providers for chaining model calls and tool use are Modal, Baseten, Fireworks AI, CoreWeave, and Databricks AI Runtime. |
| google-ai-mode | Baseten | Baseten * * Best For: Production-grade model APIs with heavy framework integrations and custom Triton/vLLM runtimes. |
| google-ai-mode | Modal | Modal * Best For: Code-first, highly dynamic pipelines where your tools and your model inference live in the same serverless deployment graph. |
| chatgpt-search | RunPod | The best serverless GPU inference providers for AI orchestration are generally Runpod, Modal, Baseten, Fireworks AI, Together AI, and fal. |
| chatgpt-search | Modal | The best serverless GPU inference providers for AI orchestration are generally Runpod, Modal, Baseten, Fireworks AI, Together AI, and fal. |
| perplexity | Together AI | For chaining model calls and tool use, Together AI and Fireworks AI are strong starting points: both offer managed serverless inference and fit naturally into common orchestration stacks. |
| google-ai | Modal | Modal Best For: Code-first pipeline execution, custom tool environments, and complex multi-model pipelines. |
| bing-copilot-search | Modal | ...st iteration on prompt templates and sampling parameters without redeploying, the best developer experiences today come from Modal, RunPod, and Fireworks AI. Modal is the most “Pythonic” and code-first, RunPod excels at container flexibility with quick... |
| google-ai-mode | Together AI | Together AI * The Experience: Together AI provides a robust web dashboard featuring a fully interactive Playground alongside standard OpenAI-compatible serverless APIs. |
| chatgpt-search | Modal | For your use case, I'd put Modal, RunPod Serverless, Replicate, and Baseten at the top of the shortlist, but for slightly different reasons. |
| chatgpt-search | RunPod | For your use case, I'd put Modal, RunPod Serverless, Replicate, and Baseten at the top of the shortlist, but for slightly different reasons. |
| chatgpt-search | Replicate | For your use case, I'd put Modal, RunPod Serverless, Replicate, and Baseten at the top of the shortlist, but for slightly different reasons. |



## Trend

Visibility delta: 0
Avg position delta: Not available
Citation count delta: 0