LLM Reference

Mistral Large 2 vs Qwen3.5-35B-A3B

Mistral Large 2 (2025) and Qwen3.5-35B-A3B (2026) are frontier reasoning models from MistralAI and Alibaba. Mistral Large 2 ships a 128k-token context window, while Qwen3.5-35B-A3B ships a 262k-token context window. On MMLU PRO, Qwen3.5-35B-A3B leads by 15.6 pts. On pricing, Qwen3.5-35B-A3B costs $0.14/1M input tokens versus $0.48/1M 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.

Qwen3.5-35B-A3B is ~245% cheaper at $0.14/1M; pay for Mistral Large 2 only for vision-heavy evaluation.

Decision scorecard

Local evidence first
SignalMistral Large 2Qwen3.5-35B-A3B
Best formultimodal apps, tool-calling agents, and provider-routed productionreasoning-heavy apps, tool-calling agents, and provider-routed production
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window128k262k
Cheapest output$2.40/1M tokens$1/1M tokens
Provider routes3 tracked2 tracked
Shared benchmarks1 sharedMMLU PRO leader

Decision tradeoffs

Choose Mistral Large 2 when...
  • Mistral Large 2 has broader tracked provider coverage for fallback and route flexibility.
  • Mistral Large 2 uniquely exposes Vision and Multimodal in local model data.
  • Local decision data tags Mistral Large 2 for Coding, RAG, and Agents.
Choose Qwen3.5-35B-A3B when...
  • Qwen3.5-35B-A3B holds a shared-benchmark lead on MMLU PRO, ahead by 15.6 points.
  • Qwen3.5-35B-A3B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-35B-A3B has the lower cheapest tracked output price at $1/1M tokens.
  • Qwen3.5-35B-A3B uniquely exposes Reasoning 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 Qwen3.5-35B-A3B

Mistral Large 2

$984

Cheapest tracked route/tier: AWS Bedrock

Qwen3.5-35B-A3B

$361

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $623. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Mistral Large 2 -> Qwen3.5-35B-A3B
  • No overlapping tracked provider route is sourced for Mistral Large 2 and Qwen3.5-35B-A3B; plan for SDK, billing, or endpoint changes.
  • Qwen3.5-35B-A3B is $1.40/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision and Multimodal before moving production traffic.
  • Qwen3.5-35B-A3B adds Reasoning in local capability data.
Qwen3.5-35B-A3B -> Mistral Large 2
  • No overlapping tracked provider route is sourced for Qwen3.5-35B-A3B and Mistral Large 2; plan for SDK, billing, or endpoint changes.
  • Mistral Large 2 is $1.40/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Reasoning before moving production traffic.
  • Mistral Large 2 adds Vision and Multimodal in local capability data.

Specs

Specification
Released2025-11-252026-02-24
Context window128k262k
Parameters123B35B
ArchitectureDecoder OnlyMixture of Experts
LicenseMistral LicenseApache 2.0OSI-approved
OpennessOpen weightsOpen source
WeightsUnknownAvailable
CodeUnknownUnknown
Commercial useCommercial use: non-commercialCommercial use: permitted
Knowledge cutoff2025-07-

Pricing and availability

Pricing attributeMistral Large 2Qwen3.5-35B-A3B
Input price$0.48/1M tokens$0.14/1M tokens
Output price$2.40/1M tokens$1/1M tokens
Providers

Capabilities

CapabilityMistral Large 2Qwen3.5-35B-A3B
VisionYesNo
MultimodalYesNo
ReasoningNoYes
JSON / Tool useYesYes
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkMistral Large 2Qwen3.5-35B-A3B
MMLU PRO69.785.3

Continue comparing

Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.