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Claude Opus 4.7 vs Qwen2.5 Coder 32B Instruct

Claude Opus 4.7 leads Qwen2.5 Coder 32B Instruct on the Artificial Analysis Intelligence Index, 40.7 to 6.7, and Qwen2.5 Coder 32B Instruct costs 25.0x less per output token ($1.00 vs $25.00 per million). Updated October 22, 2026; 26 benchmarks have a result for both.

Claude Opus 4.7Anthropic
Coding
67.5
Overall
71.6
Output $/M
$25.00
26
Qwen2.5 Coder 32B InstructQwen
Coding
No data
Overall
No data
Output $/M
$1.00
0
vs boards won of 26 shared

Claude Opus 4.7 or Qwen2.5 Coder 32B Instruct: which to pick

Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; Qwen2.5 Coder 32B Instruct has none, so the two cannot be ranked on coding.

Pick Qwen2.5 Coder 32B Instruct for output tokens 25.0x cheaper ($1.00 vs $25.00 per million).

Shared results
26
Claude Opus 4.7 only
77
Qwen2.5 Coder 32B Instruct only
9
Like-for-like categories
6 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
Claude Opus 4.7 67.5 from 4 benchmarks, Qwen2.5 Coder 32B Instruct not benchmarked.
Widest category
General, 47.1 points apart on average over 11 shared benchmarks.
Widest single gap
LMArena Text: entertainment and media: Claude Opus 4.7 1474 against Qwen2.5 Coder 32B Instruct 1150, 53.9 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.7 $25.00 against Qwen2.5 Coder 32B Instruct $1.00 per million output tokens, 25.0x apart.
Context window
Claude Opus 4.7 takes 1M tokens, Qwen2.5 Coder 32B Instruct 33K.

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
CategoryClaude Opus 4.7BarsQwen2.5 Coder 32B InstructTies
Coding20
Intelligence20
Reasoning50
Math20
Knowledge40
General110
All shared boards260
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
Aider polyglotNot measured16.4%Only Qwen2.5 Coder 32B Instruct measured
SWE-bench VerifiedNot measured47.0%Only Qwen2.5 Coder 32B Instruct measured
LMArena WebDev1558Not measuredOnly Claude Opus 4.7 measured
AA Coding Index73.6Not measuredOnly Claude Opus 4.7 measured
LiveCodeBench (Vals AI)85.1%Not measuredOnly Claude Opus 4.7 measured
SWE-bench Verified (Vals AI)82.0%Not measuredOnly Claude Opus 4.7 measured
Vibe Code Bench (Vals AI)71.0%Not measuredOnly Claude Opus 4.7 measured
Code migration (Vals AI)43.9%Not measuredOnly Claude Opus 4.7 measured
ProgramBench (Vals AI)0.0%Not measuredOnly Claude Opus 4.7 measured
Terminal-Bench 2.1 (Vals AI)68.5%Not measuredOnly Claude Opus 4.7 measured
LiveCodeBench (Artificial Analysis run)Not measured29.5%Only Qwen2.5 Coder 32B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)54.5%Not measuredOnly Claude Opus 4.7 measured
Terminal-Bench80.2%Not measuredOnly Claude Opus 4.7 measured
FrontierCode38.5%Not measuredOnly Claude Opus 4.7 measured
GSO-Bench44.1%Not measuredOnly Claude Opus 4.7 measured
WeirdML76.4%Not measuredOnly Claude Opus 4.7 measured
MirrorCode31.1%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: coding15191276Claude Opus 4.7
LMArena Text: software and IT15161261Claude Opus 4.7
LMArena WebDev: React1560Not measuredOnly Claude Opus 4.7 measured
LMArena WebDev: HTML1554Not measuredOnly Claude Opus 4.7 measured
LMArena WebDev: from an image1577Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
AA Intelligence Index40.76.7Claude Opus 4.7
Epoch Capabilities Index156.8119.5Claude Opus 4.7
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Agentic work benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
AA Agentic Index38.6Not measuredOnly Claude Opus 4.7 measured
Finance Agent (Vals AI)51.5%Not measuredOnly Claude Opus 4.7 measured
Tax Agent Bench (Vals AI)23.7%Not measuredOnly Claude Opus 4.7 measured
Legal Research Bench (Vals AI)38.5%Not measuredOnly Claude Opus 4.7 measured
Excel Modeling Benchmark (Vals AI)63.7%Not measuredOnly Claude Opus 4.7 measured
τ²-Bench Telecom88.6%Not measuredOnly Claude Opus 4.7 measured
APEX-Agents49.2%Not measuredOnly Claude Opus 4.7 measured
OSWorld 2.018.2%Not measuredOnly Claude Opus 4.7 measured
PostTrainBench28.6%Not measuredOnly Claude Opus 4.7 measured
Vending-Bench 2$10,937Not measuredOnly Claude Opus 4.7 measured
LMArena Search1230Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
GPQA Diamond90.2%Not measuredOnly Claude Opus 4.7 measured
MMMU Pro (Vals AI)85.5%Not measuredOnly Claude Opus 4.7 measured
GPQA Diamond (Artificial Analysis run)91.4%41.7%Claude Opus 4.7
Humanity's Last Exam (Artificial Analysis run)42.3%3.5%Claude Opus 4.7
GPQA Diamond (Epoch AI run)90.2%Not measuredOnly Claude Opus 4.7 measured
ARC-AGI93.5%Not measuredOnly Claude Opus 4.7 measured
ARC-AGI-275.8%Not measuredOnly Claude Opus 4.7 measured
SimpleBench61.7%Not measuredOnly Claude Opus 4.7 measured
Chess puzzles41.0%Not measuredOnly Claude Opus 4.7 measured
Mystery game puzzles28.0%Not measuredOnly Claude Opus 4.7 measured
EBR-bench19.0%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: hard prompts15061251Claude Opus 4.7
LMArena Text: expert15211221Claude Opus 4.7
LMArena Text: hard prompts in English15081269Claude Opus 4.7
LMArena Vision: diagrams1336Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: homework1337Not measuredOnly Claude Opus 4.7 measured
Kagi LLM Benchmark80.7%Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
AIME96.3%Not measuredOnly Claude Opus 4.7 measured
OTIS Mock AIME97.8%Not measuredOnly Claude Opus 4.7 measured
FrontierMath, tiers 1 to 370.2%Not measuredOnly Claude Opus 4.7 measured
FrontierMath, tier 431.7%Not measuredOnly Claude Opus 4.7 measured
ProofBench54.0%Not measuredOnly Claude Opus 4.7 measured
GSM8KNot measured93.0%Only Qwen2.5 Coder 32B Instruct measured
LMArena Text: math14981251Claude Opus 4.7
LMArena Text: mathematical work15091243Claude Opus 4.7
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
MMLU Pro89.9%Not measuredOnly Claude Opus 4.7 measured
LegalBench (Vals AI)85.3%Not measuredOnly Claude Opus 4.7 measured
CaseLaw (Vals AI)68.4%Not measuredOnly Claude Opus 4.7 measured
CorpFin (Vals AI)66.1%Not measuredOnly Claude Opus 4.7 measured
TaxEval (Vals AI)75.3%Not measuredOnly Claude Opus 4.7 measured
MortgageTax (Vals AI)70.3%Not measuredOnly Claude Opus 4.7 measured
MedCode (Vals AI)54.9%Not measuredOnly Claude Opus 4.7 measured
MMLU Pro (Artificial Analysis run)Not measured63.5%Only Qwen2.5 Coder 32B Instruct measured
SimpleQA Verified51.7%Not measuredOnly Claude Opus 4.7 measured
MMLUNot measured79.1%Only Qwen2.5 Coder 32B Instruct measured
AI2 Reasoning ChallengeNot measured70.5%Only Qwen2.5 Coder 32B Instruct measured
LMArena Text: science15081221Claude Opus 4.7
LMArena Text: medicine and healthcare14951187Claude Opus 4.7
LMArena Text: legal and government15041257Claude Opus 4.7
LMArena Text: business and finance14901224Claude Opus 4.7
FACTS Benchmark Suite45.5%Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 2 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index110
General benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
SAGE (Vals AI)56.1%Not measuredOnly Claude Opus 4.7 measured
MedScribe (Vals AI)83.0%Not measuredOnly Claude Opus 4.7 measured
Vals Multimodal Index67.4%Not measuredOnly Claude Opus 4.7 measured
IFBench58.6%Not measuredOnly Claude Opus 4.7 measured
Long context reasoning (AA-LCR)78.7%Not measuredOnly Claude Opus 4.7 measured
DTBench94.7%Not measuredOnly Claude Opus 4.7 measured
LMCA52.2%Not measuredOnly Claude Opus 4.7 measured
Furniture assembly33.3%Not measuredOnly Claude Opus 4.7 measured
ExploitBench26.5%Not measuredOnly Claude Opus 4.7 measured
HellaSwagNot measured83.0%Only Qwen2.5 Coder 32B Instruct measured
WinoGrandeNot measured80.8%Only Qwen2.5 Coder 32B Instruct measured
LMArena Text14901230Claude Opus 4.7
LMArena Text: instruction following14981223Claude Opus 4.7
LMArena Text: creative writing14861174Claude Opus 4.7
LMArena Vision1317Not measuredOnly Claude Opus 4.7 measured
LMArena Text: English14961248Claude Opus 4.7
LMArena Text: non-English14801205Claude Opus 4.7
LMArena Text: Chinese15311222Claude Opus 4.7
LMArena Text: German1495Not measuredOnly Claude Opus 4.7 measured
LMArena Text: Japanese1474Not measuredOnly Claude Opus 4.7 measured
LMArena Text: Korean1464Not measuredOnly Claude Opus 4.7 measured
LMArena Text: French1503Not measuredOnly Claude Opus 4.7 measured
LMArena Text: Spanish1494Not measuredOnly Claude Opus 4.7 measured
LMArena Text: Russian14941228Claude Opus 4.7
LMArena Text: Polish1489Not measuredOnly Claude Opus 4.7 measured
LMArena Text: multi-turn15051222Claude Opus 4.7
LMArena Text: longer queries15051251Claude Opus 4.7
LMArena Text: writing and language14921191Claude Opus 4.7
LMArena Text: entertainment and media14741150Claude Opus 4.7
LMArena Vision: English1322Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: Chinese1371Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: reading text1327Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: humor1309Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: recognizing things1278Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: creative writing1326Not measuredOnly Claude Opus 4.7 measured
LMArena Document1495Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 10 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
BenchmarkClaude Opus 4.7Qwen2.5 Coder 32B InstructLeader
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

Claude Opus 4.7$0.018Fits in one request
Qwen2.5 Coder 32B Instruct$0.0012Fits in one request

Qwen2.5 Coder 32B Instruct costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.7$0.325Fits in one request
Qwen2.5 Coder 32B Instruct$0.036Exceeds the context window

Qwen2.5 Coder 32B Instruct costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.7$1.25Fits in one request
Qwen2.5 Coder 32B Instruct$0.142Exceeds the context window

Qwen2.5 Coder 32B Instruct 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 Claude Opus 4.7 and Qwen2.5 Coder 32B Instruct
SpecificationAnthropic Claude Opus 4.7Qwen2.5 Coder 32B Instruct
MakerAnthropicQwen
WeightsNo public weights listedOpen weights
ReleasedApril 16, 2026November 11, 2024
Context window1M33K
Input $/Mtok$5.00$0.66
Output $/Mtok$25.00$1.00
Coding index67.5Not benchmarked
Independent measurements behind it40
Cost per solved task$2.95Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.7 better than Qwen2.5 Coder 32B Instruct for coding?

Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; Qwen2.5 Coder 32B Instruct has none, so the two cannot be ranked on coding. Pick Qwen2.5 Coder 32B Instruct for output tokens 25.0x cheaper ($1.00 vs $25.00 per million).

Which is cheaper, Claude Opus 4.7 or Qwen2.5 Coder 32B Instruct?

Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens; Qwen2.5 Coder 32B Instruct costs $0.66 and $1.00. Cost per solved task is known for Claude Opus 4.7 only.

Which has the bigger context window, Claude Opus 4.7 or Qwen2.5 Coder 32B Instruct?

Claude Opus 4.7, with 1M tokens against 33K.

How many benchmarks is the Claude Opus 4.7 vs Qwen2.5 Coder 32B Instruct comparison based on?

26 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.7's coding index rests on 4 independent benchmarks and Qwen2.5 Coder 32B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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