Mistral Small 3 vs Together AI Qwen2-72B-Instruct
Mistral Small 3 (2025) and Together AI Qwen2-72B-Instruct (2024) are compact production models from MistralAI and Alibaba. Mistral Small 3 ships a 33K-token context window, while Together AI Qwen2-72B-Instruct ships a 33K-token context window. On pricing, Mistral Small 3 costs $0.1/1M input tokens versus $0.7/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mistral Small 3 is ~600% cheaper at $0.1/1M; pay for Together AI Qwen2-72B-Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Mistral Small 3 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Decision fit | Agents, Classification, and JSON / Tool use | Classification and JSON / Tool use |
| Context window | 33K | 33K |
| Cheapest output | $0.3/1M tokens | $0.7/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Mistral Small 3 has the lower cheapest tracked output price at $0.3/1M tokens.
- Mistral Small 3 uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Mistral Small 3 for Agents, Classification, and JSON / Tool use.
- Local decision data tags Together AI Qwen2-72B-Instruct for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Mistral Small 3
$155
Cheapest tracked route: Together AI
Together AI Qwen2-72B-Instruct
$735
Cheapest tracked route: Together AI
Estimated monthly gap: $580. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Together AI Qwen2-72B-Instruct is $0.4/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Mistral Small 3 is $0.4/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Mistral Small 3 adds Function calling and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-01 | 2024-06-07 |
| Context window | 33K | 33K |
| Parameters | — | 72B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | 2023-10 | - |
Pricing and availability
| Pricing attribute | Mistral Small 3 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Input price | $0.1/1M tokens | $0.7/1M tokens |
| Output price | $0.3/1M tokens | $0.7/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Small 3 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: Mistral Small 3 and tool use: Mistral Small 3. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Mistral Small 3 lists $0.1/1M input and $0.3/1M output tokens, while Together AI Qwen2-72B-Instruct lists $0.7/1M input and $0.7/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Small 3 lower by about $0.54 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Mistral Small 3 when provider fit and lower input-token cost are central to the workload. Choose Together AI Qwen2-72B-Instruct when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Mistral Small 3 or Together AI Qwen2-72B-Instruct?
Mistral Small 3 supports 33K tokens, while Together AI Qwen2-72B-Instruct supports 33K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Mistral Small 3 or Together AI Qwen2-72B-Instruct?
Mistral Small 3 is cheaper on tracked token pricing. Mistral Small 3 costs $0.1/1M input and $0.3/1M output tokens. Together AI Qwen2-72B-Instruct costs $0.7/1M input and $0.7/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Small 3 or Together AI Qwen2-72B-Instruct open source?
Mistral Small 3 is listed under Open Source. Together AI Qwen2-72B-Instruct is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for function calling, Mistral Small 3 or Together AI Qwen2-72B-Instruct?
Mistral Small 3 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, Mistral Small 3 or Together AI Qwen2-72B-Instruct?
Mistral Small 3 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Mistral Small 3 and Together AI Qwen2-72B-Instruct?
Mistral Small 3 is available on Together AI. Together AI Qwen2-72B-Instruct is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
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Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.