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Claude Opus 4.7 vs Qwen3 Coder 30B A3B Instruct

Updated October 21, 2026. 7 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Claude Opus 4.7Anthropic
Coding
51.1
Overall
40.7
Output $/M
$25.00
7
Qwen3 Coder 30B A3B InstructQwen
Coding
60.4
Overall
9.6
Output $/M
$0.28
0
vs boards won of 7 shared

Decision reading

Pick Qwen3 Coder 30B A3B Instruct for coding: it scores 60.4 on the Vibe Coding Index against 51.1 for Claude Opus 4.7.

Pick Claude Opus 4.7 when the context window is larger, 1M against 262K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Shared results
7
Claude Opus 4.7 only
94
Qwen3 Coder 30B A3B Instruct only
9
Like-for-like categories
5 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 51.1 from 1 benchmark, Qwen3 Coder 30B A3B Instruct 60.4 from 1 benchmark.
Widest category
Agentic work, 54.1 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Claude Opus 4.7 88.6% against Qwen3 Coder 30B A3B Instruct 34.5%, 54.1 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.7 $25.00 against Qwen3 Coder 30B A3B Instruct $0.28 per million output tokens, 89.3x apart.
Context window
Claude Opus 4.7 takes 1M tokens, Qwen3 Coder 30B A3B Instruct 262K.

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 4.7BarsQwen3 Coder 30B A3B InstructTies
Coding10
Intelligence10
Agentic work10
Reasoning20
General20
All shared boards70
CodingLike-for-likeFour of these boards feed the Vibe Coding Index10
Coding benchmarks for Claude Opus 4.7 and Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B InstructLeader
SWE-bench VerifiedNot measured60.4%Only Qwen3 Coder 30B A3B Instruct measured
SWE-bench LiteNot measured49.7%Only Qwen3 Coder 30B A3B 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 measured40.3%Only Qwen3 Coder 30B A3B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)54.5%15.2%Claude Opus 4.7
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: coding1519Not measuredOnly Claude Opus 4.7 measured
LMArena Text: software and IT1516Not measuredOnly Claude Opus 4.7 measured
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 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 4.7 and Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B InstructLeader
AA Intelligence Index40.79.6Claude Opus 4.7
Epoch Capabilities Index156.8Not measuredOnly Claude Opus 4.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Claude Opus 4.7 and Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B 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%34.5%Claude Opus 4.7
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 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for Claude Opus 4.7 and Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B 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%51.6%Claude Opus 4.7
Humanity's Last Exam (Artificial Analysis run)42.3%3.8%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 prompts1506Not measuredOnly Claude Opus 4.7 measured
LMArena Text: expert1521Not measuredOnly Claude Opus 4.7 measured
LMArena Text: hard prompts in English1508Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: diagrams1336Not measuredOnly Claude Opus 4.7 measured
LMArena Vision: homework1337Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 5 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Math benchmarks for Claude Opus 4.7 and Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B InstructLeader
AIME96.3%Not measuredOnly Claude Opus 4.7 measured
AA Math IndexNot measured29.0Only Qwen3 Coder 30B A3B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured29.0%Only Qwen3 Coder 30B A3B Instruct 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
LMArena Text: math1498Not measuredOnly Claude Opus 4.7 measured
LMArena Text: mathematical work1509Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 4 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Knowledge benchmarks for Claude Opus 4.7 and Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B 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 measured70.6%Only Qwen3 Coder 30B A3B Instruct measured
SimpleQA Verified51.7%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: science1508Not measuredOnly Claude Opus 4.7 measured
LMArena Text: medicine and healthcare1495Not measuredOnly Claude Opus 4.7 measured
LMArena Text: legal and government1504Not measuredOnly Claude Opus 4.7 measured
LMArena Text: business and finance1490Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Web design benchmarks for Claude Opus 4.7 and Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B InstructLeader
Design Arena: websitesNot measured1087Only Qwen3 Coder 30B A3B Instruct measured
Design Arena: UI componentsNot measured1046Only Qwen3 Coder 30B A3B Instruct measured
Design Arena: data vizNot measured1085Only Qwen3 Coder 30B A3B Instruct measured
Neither model has a result on the other 6 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for Claude Opus 4.7 and Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B 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%32.7%Claude Opus 4.7
Long context reasoning (AA-LCR)78.7%32.7%Claude Opus 4.7
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
LMArena Text1490Not measuredOnly Claude Opus 4.7 measured
LMArena Text: instruction following1498Not measuredOnly Claude Opus 4.7 measured
LMArena Text: creative writing1486Not measuredOnly Claude Opus 4.7 measured
LMArena Vision1317Not measuredOnly Claude Opus 4.7 measured
LMArena Text: English1496Not measuredOnly Claude Opus 4.7 measured
LMArena Text: non-English1480Not measuredOnly Claude Opus 4.7 measured
LMArena Text: Chinese1531Not measuredOnly Claude Opus 4.7 measured
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: Russian1494Not measuredOnly Claude Opus 4.7 measured
LMArena Text: Polish1489Not measuredOnly Claude Opus 4.7 measured
LMArena Text: multi-turn1505Not measuredOnly Claude Opus 4.7 measured
LMArena Text: longer queries1505Not measuredOnly Claude Opus 4.7 measured
LMArena Text: writing and language1492Not measuredOnly Claude Opus 4.7 measured
LMArena Text: entertainment and media1474Not measuredOnly Claude Opus 4.7 measured
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 12 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 Qwen3 Coder 30B A3B Instruct
BenchmarkClaude Opus 4.7Qwen3 Coder 30B A3B 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
Qwen3 Coder 30B A3B Instruct$0.0002Fits in one request

Qwen3 Coder 30B A3B Instruct costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.7$0.325Fits in one request
Qwen3 Coder 30B A3B Instruct$0.0043Fits in one request

Qwen3 Coder 30B A3B Instruct costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.7$1.25Fits in one request
Qwen3 Coder 30B A3B Instruct$0.017Fits in one request

Qwen3 Coder 30B A3B 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 Qwen3 Coder 30B A3B Instruct
SpecificationAnthropic Claude Opus 4.7Qwen3 Coder 30B A3B Instruct
MakerAnthropicQwen
WeightsNo public weights listedOpen weights
ReleasedApril 16, 2026July 31, 2025
Context window1M262K
Input $/Mtok$5.00$0.07
Output $/Mtok$25.00$0.28
Coding index51.160.4
Independent measurements behind it11
Cost per solved task$2.95Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.7 better than Qwen3 Coder 30B A3B Instruct for coding?

Pick Qwen3 Coder 30B A3B Instruct for coding: it scores 60.4 on the Vibe Coding Index against 51.1 for Claude Opus 4.7. Pick Claude Opus 4.7 when the context window is larger, 1M against 262K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, Claude Opus 4.7 or Qwen3 Coder 30B A3B Instruct?

Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens; Qwen3 Coder 30B A3B Instruct costs $0.07 and $0.28. Cost per solved task is known for Claude Opus 4.7 only.

Which has the bigger context window, Claude Opus 4.7 or Qwen3 Coder 30B A3B Instruct?

Claude Opus 4.7, with 1M tokens against 262K.

How many benchmarks is the Claude Opus 4.7 vs Qwen3 Coder 30B A3B Instruct comparison based on?

7 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.7's coding index rests on 1 independent benchmark and Qwen3 Coder 30B A3B Instruct's on 1. Where only one model has a result, the page says so instead of naming a winner.

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