Mixtral 8x7B Instruct v0.1 vs Qwen2.5-72B-Instruct
Mixtral 8x7B Instruct v0.1 (2023) and Qwen2.5-72B-Instruct (2024) are compact production models from MistralAI and Alibaba. Mixtral 8x7B Instruct v0.1 ships a 33k-token context window, while Qwen2.5-72B-Instruct ships a 128k-token context window. On pricing, Mixtral 8x7B Instruct v0.1 costs $0.15/1M input tokens versus $0.18/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Qwen2.5-72B-Instruct is safer overall; choose Mixtral 8x7B Instruct v0.1 when provider fit matters.
Decision scorecard
Local evidence first| Signal | Mixtral 8x7B Instruct v0.1 | Qwen2.5-72B-Instruct |
|---|---|---|
| Best for | provider-routed production | provider-routed production |
| Decision fit | General | Coding, RAG, and Long context |
| Context window | 33k | 128k |
| Cheapest output | $0.45/1M tokens | $0.54/1M tokens |
| Provider routes | 5 tracked | 7 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Mixtral 8x7B Instruct v0.1 has the lower cheapest tracked output price at $0.45/1M tokens.
- Qwen2.5-72B-Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen2.5-72B-Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen2.5-72B-Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Qwen2.5-72B-Instruct for Coding, RAG, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Mixtral 8x7B Instruct v0.1
$233
Cheapest tracked route/tier: DeepInfra
Qwen2.5-72B-Instruct
$279
Cheapest tracked route/tier: Chutes AI
Estimated monthly gap: $46.50. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on DeepInfra; start route-level A/B tests there.
- Qwen2.5-72B-Instruct is $0.09/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen2.5-72B-Instruct adds Structured outputs in local capability data.
- Provider overlap exists on DeepInfra; start route-level A/B tests there.
- Mixtral 8x7B Instruct v0.1 is $0.09/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-12-10 | 2024-06-07 |
| Context window | 33k | 128k |
| Parameters | 56B | 72.7B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Mixtral 8x7B Instruct v0.1 | Qwen2.5-72B-Instruct |
|---|---|---|
| Input price | $0.15/1M tokens | $0.18/1M tokens |
| Output price | $0.45/1M tokens | $0.54/1M tokens |
| Providers |
Capabilities
| Capability | Mixtral 8x7B Instruct v0.1 | Qwen2.5-72B-Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Qwen2.5-72B-Instruct. Both models share the core language-model surface, 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, Mixtral 8x7B Instruct v0.1 lists $0.15/1M input and $0.45/1M output tokens on the cheapest tracked provider, while Qwen2.5-72B-Instruct lists $0.18/1M input and $0.54/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x7B Instruct v0.1 lower by about $0.05 per million blended tokens. Availability is 5 providers versus 7, so concentration risk also matters.
Choose Mixtral 8x7B Instruct v0.1 when provider fit and lower input-token cost are central to the workload. Choose Qwen2.5-72B-Instruct when long-context analysis, larger context windows, and broader provider choice 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, Mixtral 8x7B Instruct v0.1 or Qwen2.5-72B-Instruct?
Qwen2.5-72B-Instruct supports 128k tokens, while Mixtral 8x7B Instruct v0.1 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, Mixtral 8x7B Instruct v0.1 or Qwen2.5-72B-Instruct?
Mixtral 8x7B Instruct v0.1 is cheaper on tracked token pricing. Mixtral 8x7B Instruct v0.1 costs $0.15/1M input and $0.45/1M output tokens. Qwen2.5-72B-Instruct costs $0.18/1M input and $0.54/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mixtral 8x7B Instruct v0.1 or Qwen2.5-72B-Instruct open source?
Mixtral 8x7B Instruct v0.1 is listed under Apache 2.0. Qwen2.5-72B-Instruct is listed under Apache 2.0. 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 structured outputs, Mixtral 8x7B Instruct v0.1 or Qwen2.5-72B-Instruct?
Qwen2.5-72B-Instruct has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Mixtral 8x7B Instruct v0.1 and Qwen2.5-72B-Instruct?
Mixtral 8x7B Instruct v0.1 is available on Together AI, OctoML (Deprecated), AWS Bedrock, IBM watsonx, and DeepInfra. Qwen2.5-72B-Instruct is available on DeepInfra, OpenRouter, Fireworks AI, Novita AI, and Chutes AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Mixtral 8x7B Instruct v0.1 over Qwen2.5-72B-Instruct?
Qwen2.5-72B-Instruct is safer overall; choose Mixtral 8x7B Instruct v0.1 when provider fit matters. If your workload also depends on provider fit, start with Mixtral 8x7B Instruct v0.1; if it depends on long-context analysis, run the same evaluation with Qwen2.5-72B-Instruct.
Continue comparing
Last reviewed: 2026-06-01. Data sourced from public model cards and provider documentation.