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Qwen3 235B A22B Instruct 2507 vs Extract

Updated October 22, 2026; no benchmark has tested both models yet.

Qwen3 235B A22B Instruct 2507Qwen
Coding
No data
Overall
No data
Output $/M
$0.75
S ExtractScaledown
Coding
No data
Overall
No data
Output $/M
No data
vs 262K vs 1M context window. Extract fits 3.8x more.

Qwen3 235B A22B Instruct 2507 or Extract: which to pick

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

Compare them on price, context and the boards below.

No benchmark has tested both yet. Qwen3 235B A22B Instruct 2507 has results on LiveCodeBench (Artificial Analysis run), SciCode and Terminal-Bench Hard (Artificial Analysis run); Extract 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
Qwen3 235B A22B Instruct 2507 not benchmarked, Extract 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
Qwen3 235B A22B Instruct 2507 $0.75 against Extract Free per million output tokens.
Context window
Qwen3 235B A22B Instruct 2507 takes 262K tokens, Extract 1M.

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 Index4 boards measured
Coding benchmarks for Qwen3 235B A22B Instruct 2507 and Extract
BenchmarkQwen3 235B A22B Instruct 2507ExtractLeader
LiveCodeBench (Artificial Analysis run)78.8%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
SciCode41.4%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)15.2%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
WeirdML38.7%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 35 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for Qwen3 235B A22B Instruct 2507 and Extract
BenchmarkQwen3 235B A22B Instruct 2507ExtractLeader
AA Intelligence Index12.0Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Agentic work benchmarks for Qwen3 235B A22B Instruct 2507 and Extract
BenchmarkQwen3 235B A22B Instruct 2507ExtractLeader
τ²-Bench Telecom53.2%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Berkeley Function Calling Leaderboard (BFCL)52.1%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
Reasoning benchmarks for Qwen3 235B A22B Instruct 2507 and Extract
BenchmarkQwen3 235B A22B Instruct 2507ExtractLeader
GPQA Diamond (Artificial Analysis run)79.0%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Humanity's Last Exam (Artificial Analysis run)15.9%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
ARC-AGI11.0%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
ARC-AGI-21.3%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 18 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Math benchmarks for Qwen3 235B A22B Instruct 2507 and Extract
BenchmarkQwen3 235B A22B Instruct 2507ExtractLeader
AA Math Index91.0Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
AIME 2025 (Artificial Analysis run)91.0%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 11 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Knowledge benchmarks for Qwen3 235B A22B Instruct 2507 and Extract
BenchmarkQwen3 235B A22B Instruct 2507ExtractLeader
MMLU Pro (Artificial Analysis run)84.3%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 17 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
Web design benchmarks for Qwen3 235B A22B Instruct 2507 and Extract
BenchmarkQwen3 235B A22B Instruct 2507ExtractLeader
Design Arena: websites1058Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Design Arena: UI components962Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Design Arena: game dev951Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Design Arena: data viz1070Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Design Arena: 3D994Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Design Arena: all code categories1038Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 3 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
General benchmarks for Qwen3 235B A22B Instruct 2507 and Extract
BenchmarkQwen3 235B A22B Instruct 2507ExtractLeader
IFBench51.2%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Long context reasoning (AA-LCR)72.0%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
DTBench78.4%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
LMCA23.5%Not measuredOnly Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 42 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

Qwen3 235B A22B Instruct 2507$0.0005Fits in one request
Extract$0.0000Fits in one request

Extract costs less

Repository review

50K input + 3K output tokens

Qwen3 235B A22B Instruct 2507$0.0097Fits in one request
Extract$0.0020Fits in one request

Extract costs less

Agent loop

200K input + 10K output tokens

Qwen3 235B A22B Instruct 2507$0.037Fits in one request
Extract$0.0080Fits in one request

Extract 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 Qwen3 235B A22B Instruct 2507 and Extract
SpecificationQwen3 235B A22B Instruct 2507ScaleDown Extract
MakerQwenScaledown
WeightsOpen weightsNo public weights listed
ReleasedJuly 21, 2025October 13, 2026
Context window262K1M
Input $/Mtok$0.15$0.04
Output $/Mtok$0.75Free
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3 235B A22B Instruct 2507 better than Extract for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, Qwen3 235B A22B Instruct 2507 or Extract?

Qwen3 235B A22B Instruct 2507 costs $0.15 per million input tokens and $0.75 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen3 235B A22B Instruct 2507 or Extract?

Extract, with 1M tokens against 262K.

Has any benchmark tested both Qwen3 235B A22B Instruct 2507 and Extract?

No benchmark has tested both yet. Qwen3 235B A22B Instruct 2507 has results on LiveCodeBench (Artificial Analysis run), SciCode and Terminal-Bench Hard (Artificial Analysis run); Extract has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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