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Mistral Large 2 vs Qwen3-30B-A3B

Mistral Large 2 (2025) and Qwen3-30B-A3B (2025) are compact production models from MistralAI and Alibaba. Mistral Large 2 ships a 128K-token context window, while Qwen3-30B-A3B ships a not-yet-sourced context window. On pricing, Qwen3-30B-A3B costs $0.08/1M input tokens versus $0.48/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.

Qwen3-30B-A3B is ~500% cheaper at $0.08/1M; pay for Mistral Large 2 only for vision-heavy evaluation.

Decision scorecard

Local evidence first
SignalMistral Large 2Qwen3-30B-A3B
Decision fitCoding, RAG, and AgentsClassification and JSON / Tool use
Context window128K
Cheapest output$2.4/1M tokens$0.28/1M tokens
Provider routes4 tracked3 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Mistral Large 2 when...
  • Mistral Large 2 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Mistral Large 2 has broader tracked provider coverage for fallback and procurement flexibility.
  • Mistral Large 2 uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags Mistral Large 2 for Coding, RAG, and Agents.
Choose Qwen3-30B-A3B when...
  • Qwen3-30B-A3B has the lower cheapest tracked output price at $0.28/1M tokens.
  • Local decision data tags Qwen3-30B-A3B for Classification and JSON / Tool use.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate Qwen3-30B-A3B

Mistral Large 2

$984

Cheapest tracked route: AWS Bedrock

Qwen3-30B-A3B

$134

Cheapest tracked route: OpenRouter

Estimated monthly gap: $850. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Mistral Large 2 -> Qwen3-30B-A3B
  • Provider overlap exists on OpenRouter and AWS Bedrock; start route-level A/B tests there.
  • Qwen3-30B-A3B is $2.12/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Qwen3-30B-A3B -> Mistral Large 2
  • Provider overlap exists on OpenRouter and AWS Bedrock; start route-level A/B tests there.
  • Mistral Large 2 is $2.12/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Mistral Large 2 adds Vision, Multimodal, and Function calling in local capability data.

Specs

Specification
Released2025-11-252025-04-28
Context window128K
Parameters123B30B
Architecturedecoder onlymixture of experts
LicenseTrueApache 2.0
Knowledge cutoff2025-07-

Pricing and availability

Pricing attributeMistral Large 2Qwen3-30B-A3B
Input price$0.48/1M tokens$0.08/1M tokens
Output price$2.4/1M tokens$0.28/1M tokens
Providers

Capabilities

CapabilityMistral Large 2Qwen3-30B-A3B
VisionYesNo
MultimodalYesNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Mistral Large 2, multimodal input: Mistral Large 2, function calling: Mistral Large 2, and tool use: Mistral Large 2. 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 Large 2 lists $0.48/1M input and $2.4/1M output tokens, while Qwen3-30B-A3B lists $0.08/1M input and $0.28/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3-30B-A3B lower by about $0.92 per million blended tokens. Availability is 4 providers versus 3, so concentration risk also matters.

Choose Mistral Large 2 when vision-heavy evaluation and broader provider choice are central to the workload. Choose Qwen3-30B-A3B when provider fit 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. 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 is cheaper, Mistral Large 2 or Qwen3-30B-A3B?

Qwen3-30B-A3B is cheaper on tracked token pricing. Mistral Large 2 costs $0.48/1M input and $2.4/1M output tokens. Qwen3-30B-A3B costs $0.08/1M input and $0.28/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Mistral Large 2 or Qwen3-30B-A3B open source?

Mistral Large 2 is listed under True. Qwen3-30B-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 vision, Mistral Large 2 or Qwen3-30B-A3B?

Mistral Large 2 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for multimodal input, Mistral Large 2 or Qwen3-30B-A3B?

Mistral Large 2 has the clearer documented multimodal input signal in this comparison. If multimodal input 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, Mistral Large 2 or Qwen3-30B-A3B?

Mistral Large 2 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 Mistral Large 2 and Qwen3-30B-A3B?

Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. Qwen3-30B-A3B is available on OpenRouter, Fireworks AI, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.