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Mistral Small 3.2 24B vs Qwen3 VL 30B A3B Thinking

Mistral Small 3.2 24B costs 3.3x less per output token than Qwen3 VL 30B A3B Thinking ($0.30 vs $1.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace Mistral Small 3.2 24B Replace Qwen3 VL 30B A3B Thinking
Mistral Small 3.2 24BMistral AI
Coding
No data
Overall
No data
Output $/M
$0.30
Qwen3 VL 30B A3B ThinkingQwen
Coding
No data
Overall
No data
Output $/M
$1.00
vs $0.30 vs $1.00 per 1M output tokens. Mistral Small 3.2 24B is 3.3x cheaper.

Mistral Small 3.2 24B or Qwen3 VL 30B A3B Thinking: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Mistral Small 3.2 24B for output tokens 3.3x cheaper ($0.30 vs $1.00 per million).

Model AMistral Small 3.2 24BMistral AINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 VL 30B A3B ThinkingQwenNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. Mistral Small 3.2 24B has results on Design Arena: websites, Design Arena: UI components and Design Arena: game dev; Qwen3 VL 30B A3B Thinking on AA Intelligence Index. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Mistral Small 3.2 24B not benchmarked, Qwen3 VL 30B A3B Thinking not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
Mistral Small 3.2 24B $0.30 against Qwen3 VL 30B A3B Thinking $1.00 per million output tokens, 3.3x apart.
Context window
Mistral Small 3.2 24B takes 256K tokens, Qwen3 VL 30B A3B Thinking 262K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for Mistral Small 3.2 24B and Qwen3 VL 30B A3B Thinking
BenchmarkMistral Small 3.2 24BQwen3 VL 30B A3B ThinkingLeader
AA Intelligence IndexNot measured9.5Only Qwen3 VL 30B A3B Thinking measured
Neither model has a result on the other 1 board here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Web design benchmarks for Mistral Small 3.2 24B and Qwen3 VL 30B A3B Thinking
BenchmarkMistral Small 3.2 24BQwen3 VL 30B A3B ThinkingLeader
Design Arena: websites896Not measuredOnly Mistral Small 3.2 24B measured
Design Arena: UI components904Not measuredOnly Mistral Small 3.2 24B measured
Design Arena: game dev889Not measuredOnly Mistral Small 3.2 24B measured
Design Arena: data viz929Not measuredOnly Mistral Small 3.2 24B measured
Design Arena: all code categories907Not measuredOnly Mistral Small 3.2 24B measured
Neither model has a result on the other 4 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Mistral Small 3.2 24B$0.0003Fits in one request
Qwen3 VL 30B A3B Thinking$0.0008Fits in one request

Mistral Small 3.2 24B costs less

Repository review

50K input + 3K output tokens

Mistral Small 3.2 24B$0.0059Fits in one request
Qwen3 VL 30B A3B Thinking$0.018Fits in one request

Mistral Small 3.2 24B costs less

Agent loop

200K input + 10K output tokens

Mistral Small 3.2 24B$0.023Fits in one request
Qwen3 VL 30B A3B Thinking$0.068Fits in one request

Mistral Small 3.2 24B costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Mistral Small 3.2 24B and Qwen3 VL 30B A3B Thinking
SpecificationMistral Small 3.2 24BQwen3 VL 30B A3B Thinking
MakerMistral AIQwen
WeightsOpen weightsOpen weights
ReleasedJune 20, 2025October 6, 2025
Context window256K262K
Input $/Mtok$0.10$0.29
Output $/Mtok$0.30$1.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mistral Small 3.2 24B better than Qwen3 VL 30B A3B Thinking for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Small 3.2 24B for output tokens 3.3x cheaper ($0.30 vs $1.00 per million).

Which is cheaper, Mistral Small 3.2 24B or Qwen3 VL 30B A3B Thinking?

Mistral Small 3.2 24B costs $0.10 per million input tokens and $0.30 per million output tokens; Qwen3 VL 30B A3B Thinking costs $0.29 and $1.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Mistral Small 3.2 24B or Qwen3 VL 30B A3B Thinking?

Qwen3 VL 30B A3B Thinking, with 262K tokens against 256K.

Has any benchmark tested both Mistral Small 3.2 24B and Qwen3 VL 30B A3B Thinking?

No benchmark has tested both yet. Mistral Small 3.2 24B has results on Design Arena: websites, Design Arena: UI components and Design Arena: game dev; Qwen3 VL 30B A3B Thinking on AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.

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