Hosted open-weight model inference
Run Llama/Qwen/DeepSeek/etc. without owning GPUs, with production DX.
At a glance — Oct 2026
Updated 2026-10-27 · forward this page: /jtbds/open-model-inference#briefScores as of 2026-09-14 (43 days old; Depot marks scores stale after 30 days). The pick is still Depot's current editorial pick; it has not been re-reviewed since. Prices below carry their own dates.
- Depot Pick
- Fireworks AI · 8.35/10 for this job (curated estimate, high confidence)
Catalog freshness, tokens/sec, OpenAI-compat DX, and pricePerf.
- Runner-up
- Together AI · 8.20/10
Scores higher than the pick on: Price / performance, Maturity / track record.
- When not to use the pick
- Need Hub-native custom model endpoints (HF) or ultra-low latency on narrow SKUs (Groq).
- Lock-in / migration
- Pick exit signals: serves open-weight models (provider tag `open-models`). Self-host fallback listed for this job: Qwen3-0.6B-Base, DeepSeek-V3.2 weights, Gemma models under the Gemma Terms of Use.
- Sourced price (usd_per_million_input_tokens)
Pick: no sourced price in this job's unit (no_matching_sourced_price).
Cheapest matching SKU: Chutes Qwen3.8-27B (Qwen/Qwen3.8-27B-TEE) $0.039 — source, as of 2026-10-27, re-checked 2026-10-27. Not the pick; not quality-adjusted.
Price history: first seen 2026-10-03 · last changed 2026-10-19 · history JSON
- Free option
- Failure modes to watch
- Runaway spend: Set a budget and a tool-call cap per task. Alert when spend jumps. Stop the run at the cap instead of summarizing a partial trace as success.
- Context overflow: If the input exceeds the window, say so and retrieve a narrower slice. Do not answer from a truncated head as if it were the whole source.
- Lost in the middle: Ask the agent to name the passage it used. Spot-check questions whose only support sits in the middle of the context, not only at the edges.
- Non-determinism: Run the task more than once and compare the end state, not a single transcript. Record the trial count next to any success rate you cite.
- Schema drift: Validate every tool call and every loaded table against the current schema. Quarantine mismatches instead of coercing them.
- Silent truncation: Tools must return whether the payload was truncated and how long the original was. Fail the task if the answer depends on the missing span.
Cite: Agent Provider Depot, Depot Pick for open-model-inference: fireworks, scores as of 2026-09-14. Agents: GET /api/decide?jtbd=open-model-inference
Free Hosted open-weight model inference options · All sourced prices, cheapest first · for local-offline agents
Fireworks AI
Catalog freshness, tokens/sec, OpenAI-compat DX, and pricePerf.
Pricing (directional): Serverless per-token + on-demand GPU; day-0 OSS model support; post-training stack. Free credits often available.
Lock-in risk: higher = more lock-in (worse). Overall already inverts this dimension.
Top pick for production open-model serving with real DX. Prefer over random GPU DIY when you want tokens not ops.
Quote for Hosted open-weight model inference
Depot Pick stays Fireworks AI. Prices below are sourced SKU rows only (as of 2026-10-27). Input and output are not blended. GET /api/quote?jtbd=open-model-inference
Pick is not a price winner. Cheapest sourced input $/1M among candidates is chutes at 0.039. The pick has no priceSortEligible input row.
- Embeddings 150M-350M params usd_per_million_input_tokens $0.016 source as of 2026-10-03
- Qwen3 8B usd_per_million_input_tokens $0.1 source as of 2026-10-03
- Embeddings up to 150M params usd_per_million_input_tokens $0.008 source as of 2026-10-03
- serverless chat models usd_per_million_input_tokens amount unavailable source as of 2026-10-03
- B200 180 GB usd_per_gpu_hour $13 source as of 2026-10-27
- B300 288 GB usd_per_gpu_hour $15 source as of 2026-10-27
- GB300 288 GB usd_per_gpu_hour $20 source as of 2026-10-27
- H100 80 GB usd_per_gpu_hour $8 source as of 2026-10-27
- H200 141 GB usd_per_gpu_hour $8 source as of 2026-10-27
- Managed training LoRA SFT up to 16B usd_per_million_train_tokens $0.5 source as of 2026-10-03
13 of 25 candidates have no sourced price row. 16 are excluded from the Input $/1M comparison (chat_completion_input). min sourced input SKU among candidates; not quality-adjusted
Sourced Input $/1M for Hosted open-weight model inference
Candidates for this job that already have a matching sourced price (chat_completion_input), cheapest first. As of 2026-10-27. Each figure is one SKU in that unit, not a blend of input and output, not a cross-modal rate, and not a Depot score. min sourced input SKU among candidates; not quality-adjusted The Depot Pick is not a price winner.
| Provider | Input $/1M | SKU | Source | As of |
|---|---|---|---|---|
| Chutes | $0.039 | Qwen3.8-27B (Qwen/Qwen3.8-27B-TEE) | pricing page | 2026-10-27 |
| Groq | $0.075 | openai/gpt-oss-20b | pricing page | 2026-10-03 |
| DeepInfra | $0.1 | Llama-3.3-70B-Instruct-Turbo | pricing page | 2026-10-03 |
| FriendliAI | $0.14 | gemma-4-31B-it | pricing page | 2026-10-03 |
| Together AI | $0.15 | GLM-5.3-Flash | pricing page | 2026-10-03 |
| SambaNova | $0.22 | gpt-oss-120b | pricing page | 2026-10-03 |
| Cerebras | $0.35 | gpt-oss-120b | pricing page | 2026-10-03 |
| Moonshot (Kimi) | $0.95 | kimi-k2.6 | pricing page | 2026-10-20 |
| OpenRouter | $2 | anthropic/claude-sonnet-5.5 | pricing page | 2026-10-03 |
Runners-up
Together AI
Best catalog breadth for OSS models. Watch minimums and lifetime spend gates before you design around a gated…
Groq
Use when latency is the product. Do not build your whole company on one Groq model SKU — they rotate.
DeepInfra
Budget open-model workhorse and one of the cheapest large-catalog hosts. Great for evals and high-volume…
Hugging Face Inference
Perfect for Hub-native workflows and custom models. For hard production latency, graduate to…
Chutes
Budget open-model overflow with a now-pinned public TEE matrix. Depot open-model production pick stays…
FriendliAI
Open-model production peer when latency/tool-calling matter. Fireworks remains depot open-model default…
When NOT to use the top pick
Need Hub-native custom model endpoints (HF) or ultra-low latency on narrow SKUs (Groq).
Full ranking (score table)
Ranked with this JTBD's weights. Scores are curated estimates unless marked otherwise. Agents: prefer /api/decide then this table for tie-breaks.
| # | Provider | Overall | Fit | $/perf | Latency | DX | As of |
|---|---|---|---|---|---|---|---|
| 1 | Fireworks AIDepot Pick | 8.3 | 8.6 | 8.8 | 8.4 | 9.0 | 2026-09-14 |
| 2 | Together AI | 8.2 | 8.5 | 9.0 | 8.0 | 8.4 | 2026-09-14 |
| 3 | Scaleway Generative APIs | 8.1 | 7.8 | 8.6 | 8.0 | 8.2 | 2026-09-14 |
| 4 | FriendliAI | 8.0 | 8.4 | 8.0 | 8.4 | 8.2 | 2026-10-01 |
| 5 | IONOS AI Model Hub | 8.0 | 7.8 | 8.4 | 8.0 | 7.8 | 2026-09-14 |
| 6 | OpenRouter | 8.0 | 8.8 | 7.8 | 7.6 | 9.2 | 2026-09-14 |
| 7 | Infomaniak AI | 8.0 | 7.4 | 8.0 | 8.2 | 7.8 | 2026-09-14 |
| 8 | Groq | 8.0 | 7.8 | 9.0 | 8.2 | 8.8 | 2026-09-14 |
| 9 | DeepInfra | 8.0 | 8.0 | 9.4 | 7.5 | 8.5 | 2026-09-14 |
| 10 | Hugging Face Inference | 8.0 | 8.4 | 7.2 | 7.4 | 8.6 | 2026-09-14 |
| 11 | DeepSeek | 8.0 | 8.8 | 9.8 | 7.8 | 8.0 | 2026-09-14 |
| 12 | Moonshot (Kimi) | 7.9 | 8.6 | 8.4 | 7.8 | 8.2 | 2026-09-14 |
| 13 | Predibase | 7.9 | 8.4 | 8.0 | 7.8 | 8.2 | 2026-09-14 |
| 14 | Replicate | 7.8 | 8.4 | 6.0 | 8.2 | 9.4 | 2026-09-14 |
| 15 | OVHcloud AI Endpoints | 7.7 | 7.2 | 8.8 | 7.8 | 7.2 | 2026-09-14 |
| 16 | NVIDIA NIM / NGC | 7.7 | 8.6 | 7.0 | 8.0 | 6.8 | 2026-10-19 |
| 17 | Cerebras | 7.6 | 8.0 | 8.2 | 7.8 | 7.5 | 2026-09-14 |
| 18 | SambaNova | 7.5 | 8.0 | 7.8 | 8.2 | 6.8 | 2026-09-14 |
| 19 | Novita AI | 7.4 | 7.2 | 9.0 | 7.0 | 7.8 | 2026-09-14 |
| 20 | STACKIT AI Model Serving | 7.4 | 7.0 | 8.0 | 7.8 | 6.5 | 2026-09-14 |
| 21 | SiliconFlow | 7.3 | 7.4 | 9.2 | 6.8 | 7.6 | 2026-09-14 |
| 22 | Lepton AI | 7.3 | 7.2 | 8.2 | 7.2 | 7.8 | 2026-09-14 |
| 23 | Hyperbolic | 7.3 | 7.0 | 8.8 | 6.8 | 8.0 | 2026-09-14 |
| 24 | Chutes | 7.3 | 7.4 | 9.2 | 6.8 | 7.6 | 2026-09-14 |
| 25 | Infermatic | 6.5 | 5.5 | 8.0 | 5.8 | 7.0 | 2026-09-14 |
Score methodology for this job
Catalog freshness, tokens/sec, OpenAI-compat DX, and pricePerf.
capabilityFit: 25%pricePerformance: 18%latencyReliability: 15%developerDx: 15%privacyPosture: 10%lockInRisk: 7%maturity: 10%