Mixtral 8x22B v0.1 vs Qwen3-235B-A22B
Mixtral 8x22B v0.1 (2024) and Qwen3-235B-A22B (2025) are compact production models from MistralAI and Alibaba. Mixtral 8x22B v0.1 ships a 64K-token context window, while Qwen3-235B-A22B ships a 128K-token context window. On Google-Proof Q&A, Qwen3-235B-A22B leads by 26.0 pts. On pricing, Qwen3-235B-A22B costs $0.4/1M input tokens versus $0.65/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3-235B-A22B is ~63% cheaper at $0.4/1M; pay for Mixtral 8x22B v0.1 only for provider fit.
Decision scorecard
Local evidence first| Signal | Mixtral 8x22B v0.1 | Qwen3-235B-A22B |
|---|---|---|
| Decision fit | Coding and Classification | Coding, RAG, and Long context |
| Context window | 64K | 128K |
| Cheapest output | $0.65/1M tokens | $1.2/1M tokens |
| Provider routes | 8 tracked | 4 tracked |
| Shared benchmarks | 2 rows | Google-Proof Q&A leader |
Decision tradeoffs
- Mixtral 8x22B v0.1 has the lower cheapest tracked output price at $0.65/1M tokens.
- Mixtral 8x22B v0.1 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mixtral 8x22B v0.1 for Coding and Classification.
- Qwen3-235B-A22B leads the largest shared benchmark signal on Google-Proof Q&A by 26.0 points.
- Qwen3-235B-A22B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3-235B-A22B uniquely exposes Structured outputs in local model data.
- Local decision data tags Qwen3-235B-A22B for Coding, RAG, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Mixtral 8x22B v0.1
$683
Cheapest tracked route: DeepInfra
Qwen3-235B-A22B
$620
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $62.50. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Qwen3-235B-A22B is $0.55/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3-235B-A22B adds Structured outputs in local capability data.
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Mixtral 8x22B v0.1 is $0.55/1M 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 | 2024-04-17 | 2025-04-29 |
| Context window | 64K | 128K |
| Parameters | 8x22B | 235B |
| Architecture | mixture of experts | decoder only |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | 2024-01 | - |
Pricing and availability
| Pricing attribute | Mixtral 8x22B v0.1 | Qwen3-235B-A22B |
|---|---|---|
| Input price | $0.65/1M tokens | $0.4/1M tokens |
| Output price | $0.65/1M tokens | $1.2/1M tokens |
| Providers |
Capabilities
| Capability | Mixtral 8x22B v0.1 | Qwen3-235B-A22B |
|---|---|---|
| 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 |
Benchmarks
| Benchmark | Mixtral 8x22B v0.1 | Qwen3-235B-A22B |
|---|---|---|
| Google-Proof Q&A | 60.1 | 86.1 |
| HumanEval | 86.2 | 92.7 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Mixtral 8x22B v0.1 at 60.1 and Qwen3-235B-A22B at 86.1, with Qwen3-235B-A22B ahead by 26.0 points; HumanEval has Mixtral 8x22B v0.1 at 86.2 and Qwen3-235B-A22B at 92.7, with Qwen3-235B-A22B ahead by 6.5 points. The largest visible gap is 26.0 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on structured outputs: Qwen3-235B-A22B. 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 8x22B v0.1 lists $0.65/1M input and $0.65/1M output tokens, while Qwen3-235B-A22B lists $0.4/1M input and $1.2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3-235B-A22B lower by about $0.01 per million blended tokens. Availability is 8 providers versus 4, so concentration risk also matters.
Choose Mixtral 8x22B v0.1 when provider fit and broader provider choice are central to the workload. Choose Qwen3-235B-A22B when long-context analysis, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Mixtral 8x22B v0.1 or Qwen3-235B-A22B?
Qwen3-235B-A22B supports 128K tokens, while Mixtral 8x22B v0.1 supports 64K 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 8x22B v0.1 or Qwen3-235B-A22B?
Qwen3-235B-A22B is cheaper on tracked token pricing. Mixtral 8x22B v0.1 costs $0.65/1M input and $0.65/1M output tokens. Qwen3-235B-A22B costs $0.4/1M input and $1.2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mixtral 8x22B v0.1 or Qwen3-235B-A22B open source?
Mixtral 8x22B v0.1 is listed under Apache 2.0. Qwen3-235B-A22B 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 8x22B v0.1 or Qwen3-235B-A22B?
Qwen3-235B-A22B 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 8x22B v0.1 and Qwen3-235B-A22B?
Mixtral 8x22B v0.1 is available on NVIDIA NIM, OctoAI API (Deprecated), Fireworks AI, DeepInfra, and Baseten API. Qwen3-235B-A22B is available on Fireworks AI, AWS Bedrock, OpenRouter, and Venice AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Mixtral 8x22B v0.1 over Qwen3-235B-A22B?
Qwen3-235B-A22B is ~63% cheaper at $0.4/1M; pay for Mixtral 8x22B v0.1 only for provider fit. If your workload also depends on provider fit, start with Mixtral 8x22B v0.1; if it depends on long-context analysis, run the same evaluation with Qwen3-235B-A22B.
Continue comparing
Last reviewed: 2026-05-20. Data sourced from public model cards and provider documentation.