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Mixtral 8x22B Instruct vs Voxtral Small 24B 2507

Voxtral Small 24B 2507 costs 20.0x less per output token than Mixtral 8x22B Instruct ($0.30 vs $6.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.

Mixtral 8x22B InstructMistral AI
Coding
No data
Overall
No data
Output $/M
$6.00
Voxtral Small 24B 2507Mistral AI
Coding
No data
Overall
No data
Output $/M
$0.30
vs $6.00 vs $0.30 per 1M output tokens. Voxtral Small 24B 2507 is 20.0x cheaper.

Mixtral 8x22B Instruct or Voxtral Small 24B 2507: which to pick

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

Pick Mixtral 8x22B Instruct for a larger context window (66K against 33K tokens).

No benchmark has tested both yet. Mixtral 8x22B Instruct has results on LiveCodeBench (Artificial Analysis run), SciCode and AA Intelligence Index; Voxtral Small 24B 2507 has none yet. 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
Mixtral 8x22B Instruct not benchmarked, Voxtral Small 24B 2507 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
Mixtral 8x22B Instruct $6.00 against Voxtral Small 24B 2507 $0.30 per million output tokens, 20.0x apart.
Context window
Mixtral 8x22B Instruct takes 66K tokens, Voxtral Small 24B 2507 33K.

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.

CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards measured
Coding benchmarks for Mixtral 8x22B Instruct and Voxtral Small 24B 2507
BenchmarkMixtral 8x22B InstructVoxtral Small 24B 2507Leader
LiveCodeBench (Artificial Analysis run)14.8%Not measuredOnly Mixtral 8x22B Instruct measured
SciCode0.0%Not measuredOnly Mixtral 8x22B Instruct measured
Neither model has a result on the other 37 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Intelligence benchmarks for Mixtral 8x22B Instruct and Voxtral Small 24B 2507
BenchmarkMixtral 8x22B InstructVoxtral Small 24B 2507Leader
AA Intelligence Index5.7Not measuredOnly Mixtral 8x22B Instruct measured
Epoch Capabilities Index122.0Not measuredOnly Mixtral 8x22B Instruct measured
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Reasoning benchmarks for Mixtral 8x22B Instruct and Voxtral Small 24B 2507
BenchmarkMixtral 8x22B InstructVoxtral Small 24B 2507Leader
GPQA Diamond (Artificial Analysis run)33.2%Not measuredOnly Mixtral 8x22B Instruct measured
Humanity's Last Exam (Artificial Analysis run)4.0%Not measuredOnly Mixtral 8x22B Instruct measured
Neither model has a result on the other 20 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Knowledge benchmarks for Mixtral 8x22B Instruct and Voxtral Small 24B 2507
BenchmarkMixtral 8x22B InstructVoxtral Small 24B 2507Leader
MMLU Pro (Artificial Analysis run)53.7%Not measuredOnly Mixtral 8x22B Instruct measured
Neither model has a result on the other 17 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
General benchmarks for Mixtral 8x22B Instruct and Voxtral Small 24B 2507
BenchmarkMixtral 8x22B InstructVoxtral Small 24B 2507Leader
DTBench55.1%Not measuredOnly Mixtral 8x22B Instruct measured
Neither model has a result on the other 45 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

Mixtral 8x22B Instruct$0.0050Fits in one request
Voxtral Small 24B 2507$0.0003Fits in one request

Voxtral Small 24B 2507 costs less

Repository review

50K input + 3K output tokens

Mixtral 8x22B Instruct$0.118Fits in one request
Voxtral Small 24B 2507$0.0059Exceeds the context window

Voxtral Small 24B 2507 costs less

Agent loop

200K input + 10K output tokens

Mixtral 8x22B Instruct$0.460Exceeds the context window
Voxtral Small 24B 2507$0.023Exceeds the context window

Voxtral Small 24B 2507 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 Mixtral 8x22B Instruct and Voxtral Small 24B 2507
SpecificationMistral Mixtral 8x22B InstructMistral Voxtral Small 24B 2507
MakerMistral AIMistral AI
WeightsOpen weightsOpen weights
ReleasedApril 17, 2024October 30, 2025
Context window66K33K
Input $/Mtok$2.00$0.10
Output $/Mtok$6.00$0.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mixtral 8x22B Instruct better than Voxtral Small 24B 2507 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mixtral 8x22B Instruct for a larger context window (66K against 33K tokens).

Which is cheaper, Mixtral 8x22B Instruct or Voxtral Small 24B 2507?

Mixtral 8x22B Instruct costs $2.00 per million input tokens and $6.00 per million output tokens; Voxtral Small 24B 2507 costs $0.10 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, Mixtral 8x22B Instruct or Voxtral Small 24B 2507?

Mixtral 8x22B Instruct, with 66K tokens against 33K.

Has any benchmark tested both Mixtral 8x22B Instruct and Voxtral Small 24B 2507?

No benchmark has tested both yet. Mixtral 8x22B Instruct has results on LiveCodeBench (Artificial Analysis run), SciCode and AA Intelligence Index; Voxtral Small 24B 2507 has none yet. Compare them on price and context instead. Data as of October 21, 2026.

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