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Qwen2.5 7B Instruct vs Extract

Updated October 21, 2026; no benchmark has tested both models yet.

Replace Qwen2.5 7B Instruct Replace Extract
Qwen2.5 7B InstructQwen
Coding
No data
Overall
No data
Output $/M
$0.20
S ExtractScaledown
Coding
No data
Overall
No data
Output $/M
No data
vs 33K vs 1M context window. Extract fits 30.5x more.

Qwen2.5 7B Instruct 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.

Model AQwen2.5 7B InstructQwenNot benchmarkedNo coding benchmarkNo cost per solved taskModel BExtractScaledownNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. Qwen2.5 7B Instruct has results on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI 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
Qwen2.5 7B Instruct 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
Qwen2.5 7B Instruct $0.20 against Extract Free per million output tokens.
Context window
Qwen2.5 7B Instruct takes 33K 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.

IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for Qwen2.5 7B Instruct and Extract
BenchmarkQwen2.5 7B InstructExtractLeader
Epoch Capabilities Index118.5Not measuredOnly Qwen2.5 7B Instruct measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Agentic work benchmarks for Qwen2.5 7B Instruct and Extract
BenchmarkQwen2.5 7B InstructExtractLeader
BALROG7.8%Not measuredOnly Qwen2.5 7B Instruct measured
Neither model has a result on the other 40 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Reasoning benchmarks for Qwen2.5 7B Instruct and Extract
BenchmarkQwen2.5 7B InstructExtractLeader
GPQA Diamond (Epoch AI run)35.5%Not measuredOnly Qwen2.5 7B Instruct measured
Neither model has a result on the other 21 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Math benchmarks for Qwen2.5 7B Instruct and Extract
BenchmarkQwen2.5 7B InstructExtractLeader
OTIS Mock AIME2.5%Not measuredOnly Qwen2.5 7B Instruct measured
Neither model has a result on the other 12 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Knowledge benchmarks for Qwen2.5 7B Instruct and Extract
BenchmarkQwen2.5 7B InstructExtractLeader
MMLU72.9%Not measuredOnly Qwen2.5 7B Instruct measured
Neither model has a result on the other 17 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
General benchmarks for Qwen2.5 7B Instruct and Extract
BenchmarkQwen2.5 7B InstructExtractLeader
DTBench47.7%Not measuredOnly Qwen2.5 7B Instruct measured
LMCA6.4%Not measuredOnly Qwen2.5 7B Instruct measured
Neither model has a result on the other 44 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

Qwen2.5 7B Instruct$0.0002Fits in one request
Extract$0.0000Fits in one request

Extract costs less

Repository review

50K input + 3K output tokens

Qwen2.5 7B Instruct$0.0056Exceeds the context window
Extract$0.0020Fits in one request

Extract costs less

Agent loop

200K input + 10K output tokens

Qwen2.5 7B Instruct$0.022Exceeds the context window
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 Qwen2.5 7B Instruct and Extract
SpecificationQwen2.5 7B InstructScaleDown Extract
MakerQwenScaledown
WeightsOpen weightsNo public weights listed
ReleasedOctober 16, 2024October 13, 2026
Context window33K1M
Input $/Mtok$0.10$0.04
Output $/Mtok$0.20Free
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen2.5 7B Instruct 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, Qwen2.5 7B Instruct or Extract?

Qwen2.5 7B Instruct costs $0.10 per million input tokens and $0.20 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, Qwen2.5 7B Instruct or Extract?

Extract, with 1M tokens against 33K.

Has any benchmark tested both Qwen2.5 7B Instruct and Extract?

No benchmark has tested both yet. Qwen2.5 7B Instruct has results on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI run); Extract has none yet. Compare them on price and context instead. Data as of October 21, 2026.

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