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Mixtral 8x22B Instruct vs Qwen3 235B A22B Thinking 2507

Qwen3 235B A22B Thinking 2507 leads Mixtral 8x22B Instruct on the Artificial Analysis Intelligence Index, 12.7 to 5.7, and Qwen3 235B A22B Thinking 2507 costs 1.7x less per output token ($3.50 vs $6.00 per million). Updated October 22, 2026; 2 benchmarks have a result for both.

Mixtral 8x22B InstructMistral AI
Coding
No data
Overall
No data
Output $/M
$6.00
0
Qwen3 235B A22B Thinking 2507Qwen
Coding
No data
Overall
52.9
Output $/M
$3.50
2
vs boards won of 2 shared

Mixtral 8x22B Instruct or Qwen3 235B A22B Thinking 2507: which to pick

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

Pick Mixtral 8x22B Instruct for work measured by AA Intelligence Index or DTBench, where it leads.

Shared results
2
Mixtral 8x22B Instruct only
6
Qwen3 235B A22B Thinking 2507 only
44
Like-for-like categories
2 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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, Qwen3 235B A22B Thinking 2507 not benchmarked.
Widest category
General, 25.1 points apart on average over 1 shared benchmark.
Widest single gap
DTBench: Mixtral 8x22B Instruct 55.1% against Qwen3 235B A22B Thinking 2507 80.3%, 25.1 points apart on a 0 to 100 scale.
Output price
Mixtral 8x22B Instruct $6.00 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 1.7x apart.
Context window
Mixtral 8x22B Instruct takes 66K tokens, Qwen3 235B A22B Thinking 2507 128K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryMixtral 8x22B InstructBarsQwen3 235B A22B Thinking 2507Ties
Intelligence01
General01
All shared boards02
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
Coding benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 2507Leader
AA Coding IndexNot measured22.1Only Qwen3 235B A22B Thinking 2507 measured
LiveCodeBench (Artificial Analysis run)14.8%Not measuredOnly Mixtral 8x22B Instruct measured
WeirdMLNot measured41.0%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: codingNot measured1424Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: software and ITNot measured1431Only Qwen3 235B A22B Thinking 2507 measured
SciCode0.0%Not measuredOnly Mixtral 8x22B Instruct measured
Neither model has a result on the other 33 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 2507Leader
AA Intelligence Index5.712.7Qwen3 235B A22B Thinking 2507
Epoch Capabilities Index122.0Not measuredOnly Mixtral 8x22B Instruct measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 2507Leader
AA Agentic IndexNot measured1.3Only Qwen3 235B A22B Thinking 2507 measured
Vending-Bench 2Not measured-$11Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Reasoning benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 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
GPQA Diamond (Epoch AI run)Not measured80.1%Only Qwen3 235B A22B Thinking 2507 measured
Mystery game puzzlesNot measured9.0%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: hard promptsNot measured1416Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: expertNot measured1463Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: hard prompts in EnglishNot measured1432Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Math benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 2507Leader
OTIS Mock AIMENot measured86.7%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: mathNot measured1412Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: mathematical workNot measured1435Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 2507Leader
MMLU Pro (Artificial Analysis run)53.7%Not measuredOnly Mixtral 8x22B Instruct measured
SimpleQA VerifiedNot measured40.4%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: scienceNot measured1433Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: medicine and healthcareNot measured1456Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: legal and governmentNot measured1415Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: business and financeNot measured1413Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 2507Leader
Design Arena: websitesNot measured1052Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: UI componentsNot measured942Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: game devNot measured956Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: data vizNot measured950Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: 3DNot measured997Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: all code categoriesNot measured1032Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
General benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 2507Leader
DTBench55.1%80.3%Qwen3 235B A22B Thinking 2507
LMCANot measured29.3%Only Qwen3 235B A22B Thinking 2507 measured
Fiction.LiveBenchNot measured75.0%Only Qwen3 235B A22B Thinking 2507 measured
Creative writing (Lech Mazur)Not measured82.4%Only Qwen3 235B A22B Thinking 2507 measured
LMArena TextNot measured1415Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: instruction followingNot measured1386Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: creative writingNot measured1384Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: EnglishNot measured1429Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: non-EnglishNot measured1397Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: ChineseNot measured1481Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: GermanNot measured1408Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: JapaneseNot measured1386Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: KoreanNot measured1375Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: SpanishNot measured1389Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: RussianNot measured1401Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: PolishNot measured1390Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: multi-turnNot measured1406Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: longer queriesNot measured1400Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: writing and languageNot measured1388Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: entertainment and mediaNot measured1370Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mixtral 8x22B Instruct and Qwen3 235B A22B Thinking 2507
BenchmarkMixtral 8x22B InstructQwen3 235B A22B Thinking 2507Leader
Neither model has a result on 5 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
Qwen3 235B A22B Thinking 2507$0.0022Fits in one request

Qwen3 235B A22B Thinking 2507 costs less

Repository review

50K input + 3K output tokens

Mixtral 8x22B Instruct$0.118Fits in one request
Qwen3 235B A22B Thinking 2507$0.033Fits in one request

Qwen3 235B A22B Thinking 2507 costs less

Agent loop

200K input + 10K output tokens

Mixtral 8x22B Instruct$0.460Exceeds the context window
Qwen3 235B A22B Thinking 2507$0.125Exceeds the context window

Qwen3 235B A22B Thinking 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 Qwen3 235B A22B Thinking 2507
SpecificationMistral Mixtral 8x22B InstructQwen3 235B A22B Thinking 2507
MakerMistral AIQwen
WeightsOpen weightsOpen weights
ReleasedApril 17, 2024July 25, 2025
Context window66K128K
Input $/Mtok$2.00$0.45
Output $/Mtok$6.00$3.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mixtral 8x22B Instruct better than Qwen3 235B A22B Thinking 2507 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mixtral 8x22B Instruct for work measured by AA Intelligence Index or DTBench, where it leads.

Which is cheaper, Mixtral 8x22B Instruct or Qwen3 235B A22B Thinking 2507?

Mixtral 8x22B Instruct costs $2.00 per million input tokens and $6.00 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for neither of them.

Which has the bigger context window, Mixtral 8x22B Instruct or Qwen3 235B A22B Thinking 2507?

Qwen3 235B A22B Thinking 2507, with 128K tokens against 66K.

How many benchmarks is the Mixtral 8x22B Instruct vs Qwen3 235B A22B Thinking 2507 comparison based on?

2 benchmarks have a result for both models as of October 22, 2026. Mixtral 8x22B Instruct's coding index rests on 0 independent benchmarks and Qwen3 235B A22B Thinking 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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