LLM Reference

Mixtral 8x7B vs Qwen3.5-35B-A3B

Mixtral 8x7B (2023) and Qwen3.5-35B-A3B (2026) are frontier reasoning models from MistralAI and Alibaba. Mixtral 8x7B ships a 32k-token context window, while Qwen3.5-35B-A3B ships a 262k-token context window. On Google-Proof Q&A, Qwen3.5-35B-A3B leads by 29.7 pts. On pricing, Qwen3.5-35B-A3B costs $0.14/1M input tokens versus $0.15/1M 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.

Pick Qwen3.5-35B-A3B for reasoning; Mixtral 8x7B is better when provider fit matters more.

Decision scorecard

Local evidence first
SignalMixtral 8x7BQwen3.5-35B-A3B
Best forprovider-routed productionreasoning-heavy apps, tool-calling agents, and provider-routed production
Decision fitCoding and ClassificationCoding, RAG, and Agents
Context window32k262k
Cheapest output$0.45/1M tokens$1/1M tokens
Provider routes18 tracked2 tracked
Shared benchmarks1 rowsGoogle-Proof Q&A leader

Decision tradeoffs

Choose Mixtral 8x7B when...
  • Mixtral 8x7B has the lower cheapest tracked output price at $0.45/1M tokens.
  • Mixtral 8x7B has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Mixtral 8x7B for Coding and Classification.
Choose Qwen3.5-35B-A3B when...
  • Qwen3.5-35B-A3B holds a shared-benchmark lead on Google-Proof Q&A, ahead by 29.7 points.
  • Qwen3.5-35B-A3B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-35B-A3B uniquely exposes Reasoning, Function calling, and Tool use in local model data.
  • Local decision data tags Qwen3.5-35B-A3B for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Mixtral 8x7B

Mixtral 8x7B

$233

Cheapest tracked route/tier: Mistral AI Studio

Qwen3.5-35B-A3B

$361

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $129. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Mixtral 8x7B -> Qwen3.5-35B-A3B
  • No overlapping tracked provider route is sourced for Mixtral 8x7B and Qwen3.5-35B-A3B; plan for SDK, billing, or endpoint changes.
  • Qwen3.5-35B-A3B is $0.55/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Qwen3.5-35B-A3B adds Reasoning, Function calling, and Tool use in local capability data.
Qwen3.5-35B-A3B -> Mixtral 8x7B
  • No overlapping tracked provider route is sourced for Qwen3.5-35B-A3B and Mixtral 8x7B; plan for SDK, billing, or endpoint changes.
  • Mixtral 8x7B is $0.55/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.

Specs

Specification
Released2023-12-112026-02-24
Context window32k262k
Parameters8x7B35B
Architecturemixture of expertsmixture of experts
LicenseApache 2.0(OSI)Apache 2.0(OSI)
OpennessOpen sourceOpen source
Commercial useCommercial use allowedCommercial use allowed
Knowledge cutoff2023-12-

Pricing and availability

Pricing attributeMixtral 8x7BQwen3.5-35B-A3B
Input price$0.15/1M tokens$0.14/1M tokens
Output price$0.45/1M tokens$1/1M tokens
Providers

Capabilities

CapabilityMixtral 8x7BQwen3.5-35B-A3B
VisionNoNo
MultimodalNoNo
ReasoningNoYes
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkMixtral 8x7BQwen3.5-35B-A3B
Google-Proof Q&A54.884.5

Deep dive

On shared benchmark coverage, Google-Proof Q&A has Mixtral 8x7B at 54.8 and Qwen3.5-35B-A3B at 84.5, with Qwen3.5-35B-A3B ahead by 29.7 points. The largest visible gap is 29.7 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 reasoning mode: Qwen3.5-35B-A3B, function calling: Qwen3.5-35B-A3B, tool use: Qwen3.5-35B-A3B, and structured outputs: Qwen3.5-35B-A3B. 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 lists $0.15/1M input and $0.45/1M output tokens on the cheapest tracked provider, while Qwen3.5-35B-A3B lists $0.14/1M input and $1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x7B lower by about $0.16 per million blended tokens. Availability is 18 providers versus 2, so concentration risk also matters.

Choose Mixtral 8x7B when provider fit and broader provider choice are central to the workload. Choose Qwen3.5-35B-A3B when reasoning depth, 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 8x7B or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B supports 262k tokens, while Mixtral 8x7B supports 32k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is cheaper, Mixtral 8x7B or Qwen3.5-35B-A3B?

Mixtral 8x7B is cheaper on tracked token pricing. Mixtral 8x7B costs $0.15/1M input and $0.45/1M output tokens. Qwen3.5-35B-A3B costs $0.14/1M input and $1/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Mixtral 8x7B or Qwen3.5-35B-A3B open source?

Mixtral 8x7B is listed under Apache 2.0. Qwen3.5-35B-A3B 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 reasoning mode, Mixtral 8x7B or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for function calling, Mixtral 8x7B or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B 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.

Where can I run Mixtral 8x7B and Qwen3.5-35B-A3B?

Mixtral 8x7B is available on Databricks Foundation Model Serving, NVIDIA NIM, GCP Vertex AI, AWS Bedrock, and OctoAI API (Deprecated). Qwen3.5-35B-A3B is available on OpenRouter and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.