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Claude Haiku 4.5 vs Qwen3 30B A3B Instruct 2507

Claude Haiku 4.5 leads Qwen3 30B A3B Instruct 2507 on the Artificial Analysis Intelligence Index, 16.9 to 7.5, and Qwen3 30B A3B Instruct 2507 costs 16.7x less per output token ($0.30 vs $5.00 per million). Updated October 22, 2026; 34 benchmarks have a result for both.

Replace Claude Haiku 4.5 Replace Qwen3 30B A3B Instruct 2507
Claude Haiku 4.5Anthropic
Coding
35.6
Overall
41.0
Output $/M
$5.00
30
Qwen3 30B A3B Instruct 2507Qwen
Coding
No data
Overall
41.5
Output $/M
$0.30
4
vs boards won of 34 shared

Claude Haiku 4.5 or Qwen3 30B A3B Instruct 2507: which to pick

Only Claude Haiku 4.5 has a coding score, 35.6 on the Vibe Coding Index; Qwen3 30B A3B Instruct 2507 has none, so the two cannot be ranked on coding.

Pick Qwen3 30B A3B Instruct 2507 for output tokens 16.7x cheaper ($0.30 vs $5.00 per million) and a larger context window (262K against 200K tokens).

Model AClaude Haiku 4.5Anthropic35.6/1004 independent benchmarks$0.56 per solved taskModel BQwen3 30B A3B Instruct 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
34
Claude Haiku 4.5 only
64
Qwen3 30B A3B Instruct 2507 only
11
Like-for-like categories
7 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 Haiku 4.5 35.6 from 4 benchmarks, Qwen3 30B A3B Instruct 2507 not benchmarked.
Widest category
Agentic work, 27.3 points apart on average over 1 shared benchmark.
Widest single gap
Berkeley Function Calling Leaderboard (BFCL): Claude Haiku 4.5 68.7% against Qwen3 30B A3B Instruct 2507 41.4%, 27.3 points apart on a 0 to 100 scale.
Output price
Claude Haiku 4.5 $5.00 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 16.7x apart.
Context window
Claude Haiku 4.5 takes 200K tokens, Qwen3 30B A3B Instruct 2507 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 Haiku 4.5BarsQwen3 30B A3B Instruct 2507Ties
Coding20
Intelligence10
Agentic work10
Reasoning40
Math30
Knowledge40
General154
All shared boards304
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 2507Leader
SWE-bench Verified66.6%Not measuredOnly Claude Haiku 4.5 measured
SWE-bench Multilingual64.7%Not measuredOnly Claude Haiku 4.5 measured
LiveBench coding48.1%Not measuredOnly Claude Haiku 4.5 measured
LMArena WebDev1330Not measuredOnly Claude Haiku 4.5 measured
AA Coding Index43.9Not measuredOnly Claude Haiku 4.5 measured
LiveCodeBench (Vals AI)41.2%Not measuredOnly Claude Haiku 4.5 measured
SWE-bench Verified (Vals AI)66.6%Not measuredOnly Claude Haiku 4.5 measured
Vibe Code Bench (Vals AI)11.4%Not measuredOnly Claude Haiku 4.5 measured
Code migration (Vals AI)7.5%Not measuredOnly Claude Haiku 4.5 measured
ProgramBench (Vals AI)0.0%Not measuredOnly Claude Haiku 4.5 measured
Terminal-Bench 2.1 (Vals AI)43.8%Not measuredOnly Claude Haiku 4.5 measured
LiveCodeBench (Artificial Analysis run)Not measured70.7%Only Qwen3 30B A3B Instruct 2507 measured
SciCodeNot measured33.0%Only Qwen3 30B A3B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured6.1%Only Qwen3 30B A3B Instruct 2507 measured
Terminal-Bench35.5%Not measuredOnly Claude Haiku 4.5 measured
WeirdML45.4%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: coding14541416Claude Haiku 4.5
LMArena Text: software and IT14391417Claude Haiku 4.5
LMArena WebDev: React1326Not measuredOnly Claude Haiku 4.5 measured
LMArena WebDev: HTML1318Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 2507Leader
AA Intelligence Index16.97.5Claude Haiku 4.5
Epoch Capabilities Index142.2Not measuredOnly Claude Haiku 4.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 2507Leader
AA Agentic Index8.0Not measuredOnly Claude Haiku 4.5 measured
LiveBench research42.2%Not measuredOnly Claude Haiku 4.5 measured
LiveBench browser40.0%Not measuredOnly Claude Haiku 4.5 measured
LiveBench long agentic11.1%Not measuredOnly Claude Haiku 4.5 measured
Finance Agent (Vals AI)31.0%Not measuredOnly Claude Haiku 4.5 measured
Tax Agent Bench (Vals AI)5.9%Not measuredOnly Claude Haiku 4.5 measured
Legal Research Bench (Vals AI)10.6%Not measuredOnly Claude Haiku 4.5 measured
Excel Modeling Benchmark (Vals AI)22.7%Not measuredOnly Claude Haiku 4.5 measured
τ²-Bench TelecomNot measured28.1%Only Qwen3 30B A3B Instruct 2507 measured
BALROG31.2%Not measuredOnly Claude Haiku 4.5 measured
DeepResearch Bench45.5%Not measuredOnly Claude Haiku 4.5 measured
Vending-Bench 2$459Not measuredOnly Claude Haiku 4.5 measured
Berkeley Function Calling Leaderboard (BFCL)68.7%41.4%Claude Haiku 4.5
MCP Atlas40.2%Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 2507Leader
GPQA Diamond72.2%Not measuredOnly Claude Haiku 4.5 measured
LiveBench reasoning61.7%Not measuredOnly Claude Haiku 4.5 measured
MMMU Pro (Vals AI)46.1%Not measuredOnly Claude Haiku 4.5 measured
GPQA Diamond (Artificial Analysis run)Not measured70.7%Only Qwen3 30B A3B Instruct 2507 measured
Humanity's Last Exam (Artificial Analysis run)Not measured10.3%Only Qwen3 30B A3B Instruct 2507 measured
GPQA Diamond (Epoch AI run)71.2%55.6%Claude Haiku 4.5
ARC-AGI47.7%Not measuredOnly Claude Haiku 4.5 measured
ARC-AGI-24.0%Not measuredOnly Claude Haiku 4.5 measured
Chess puzzles8.0%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: hard prompts14211398Claude Haiku 4.5
LMArena Text: expert14431397Claude Haiku 4.5
LMArena Text: hard prompts in English14351406Claude Haiku 4.5
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 2507Leader
AIME82.7%Not measuredOnly Claude Haiku 4.5 measured
MGSM (Vals AI)92.2%Not measuredOnly Claude Haiku 4.5 measured
AA Math IndexNot measured66.3Only Qwen3 30B A3B Instruct 2507 measured
AIME 2025 (Artificial Analysis run)Not measured66.3%Only Qwen3 30B A3B Instruct 2507 measured
OTIS Mock AIME66.7%62.2%Claude Haiku 4.5
MATH level 596.4%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: math13981394Claude Haiku 4.5
LMArena Text: mathematical work14301411Claude Haiku 4.5
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 2507Leader
MMLU Pro78.7%Not measuredOnly Claude Haiku 4.5 measured
LegalBench (Vals AI)81.2%Not measuredOnly Claude Haiku 4.5 measured
CaseLaw (Vals AI)56.5%Not measuredOnly Claude Haiku 4.5 measured
CorpFin (Vals AI)60.6%Not measuredOnly Claude Haiku 4.5 measured
TaxEval (Vals AI)67.5%Not measuredOnly Claude Haiku 4.5 measured
MortgageTax (Vals AI)62.2%Not measuredOnly Claude Haiku 4.5 measured
MedQA (Vals AI)79.6%Not measuredOnly Claude Haiku 4.5 measured
MedCode (Vals AI)32.7%Not measuredOnly Claude Haiku 4.5 measured
MMLU Pro (Artificial Analysis run)Not measured80.5%Only Qwen3 30B A3B Instruct 2507 measured
SimpleQA Verified13.2%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: science14061393Claude Haiku 4.5
LMArena Text: medicine and healthcare13941392Claude Haiku 4.5
LMArena Text: legal and government14001387Claude Haiku 4.5
LMArena Text: business and finance14001389Claude Haiku 4.5
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 2507Leader
Design Arena: websites1122Not measuredOnly Claude Haiku 4.5 measured
Design Arena: UI components1097Not measuredOnly Claude Haiku 4.5 measured
Design Arena: game dev1096Not measuredOnly Claude Haiku 4.5 measured
Design Arena: data viz1124Not measuredOnly Claude Haiku 4.5 measured
Design Arena: 3D1071Not measuredOnly Claude Haiku 4.5 measured
Design Arena: all code categories1114Not measuredOnly Claude Haiku 4.5 measured
Design Arena: SVG1025Not measuredOnly Claude Haiku 4.5 measured
Design Arena: ASCII art1140Not measuredOnly Claude Haiku 4.5 measured
LiveBench design59.9%Not measuredOnly Claude Haiku 4.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index154
General benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 2507Leader
LiveBench data analysis59.3%Not measuredOnly Claude Haiku 4.5 measured
Public Benefits Bench (Vals AI)54.3%Not measuredOnly Claude Haiku 4.5 measured
SAGE (Vals AI)31.8%Not measuredOnly Claude Haiku 4.5 measured
MedScribe (Vals AI)85.2%Not measuredOnly Claude Haiku 4.5 measured
Vals Multimodal Index42.9%Not measuredOnly Claude Haiku 4.5 measured
IFBenchNot measured50.7%Only Qwen3 30B A3B Instruct 2507 measured
Long context reasoning (AA-LCR)Not measured61.3%Only Qwen3 30B A3B Instruct 2507 measured
DTBench73.6%67.2%Claude Haiku 4.5
LMCA30.9%22.4%Claude Haiku 4.5
ExploitBench13.7%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text13971384Claude Haiku 4.5
LMArena Text: instruction following14141363Claude Haiku 4.5
LMArena Text: creative writing13711317Claude Haiku 4.5
LMArena Text: English14141391Claude Haiku 4.5
LMArena Text: non-English13771372Claude Haiku 4.5
LMArena Text: Chinese14181432Qwen3 30B A3B Instruct 2507
LMArena Text: German13741379Qwen3 30B A3B Instruct 2507
LMArena Text: Japanese13381337Claude Haiku 4.5
LMArena Text: Korean13461330Claude Haiku 4.5
LMArena Text: French14111419Qwen3 30B A3B Instruct 2507
LMArena Text: Spanish14211404Claude Haiku 4.5
LMArena Text: Russian13811369Claude Haiku 4.5
LMArena Text: Polish13431353Qwen3 30B A3B Instruct 2507
LMArena Text: multi-turn14091378Claude Haiku 4.5
LMArena Text: longer queries14271378Claude Haiku 4.5
LMArena Text: writing and language13861336Claude Haiku 4.5
LMArena Text: entertainment and media13691334Claude Haiku 4.5
LMArena Document1420Not measuredOnly Claude Haiku 4.5 measured
MultiChallenge50.5%Not measuredOnly Claude Haiku 4.5 measured
EQ-Bench 41064Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 18 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
BenchmarkClaude Haiku 4.5Qwen3 30B A3B Instruct 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

Claude Haiku 4.5$0.0035Fits in one request
Qwen3 30B A3B Instruct 2507$0.0002Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Repository review

50K input + 3K output tokens

Claude Haiku 4.5$0.065Fits in one request
Qwen3 30B A3B Instruct 2507$0.0054Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Agent loop

200K input + 10K output tokens

Claude Haiku 4.5$0.250Exceeds the context window
Qwen3 30B A3B Instruct 2507$0.021Fits in one request

Qwen3 30B A3B Instruct 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 Claude Haiku 4.5 and Qwen3 30B A3B Instruct 2507
SpecificationAnthropic Claude Haiku 4.5Qwen3 30B A3B Instruct 2507
MakerAnthropicQwen
WeightsNo public weights listedOpen weights
ReleasedOctober 15, 2025July 29, 2025
Context window200K262K
Input $/Mtok$1.00$0.09
Output $/Mtok$5.00$0.30
Coding index35.6Not benchmarked
Independent measurements behind it40
Cost per solved task$0.56Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Haiku 4.5 better than Qwen3 30B A3B Instruct 2507 for coding?

Only Claude Haiku 4.5 has a coding score, 35.6 on the Vibe Coding Index; Qwen3 30B A3B Instruct 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 30B A3B Instruct 2507 for output tokens 16.7x cheaper ($0.30 vs $5.00 per million) and a larger context window (262K against 200K tokens).

Which is cheaper, Claude Haiku 4.5 or Qwen3 30B A3B Instruct 2507?

Claude Haiku 4.5 costs $1.00 per million input tokens and $5.00 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for Claude Haiku 4.5 only.

Which has the bigger context window, Claude Haiku 4.5 or Qwen3 30B A3B Instruct 2507?

Qwen3 30B A3B Instruct 2507, with 262K tokens against 200K.

How many benchmarks is the Claude Haiku 4.5 vs Qwen3 30B A3B Instruct 2507 comparison based on?

34 benchmarks have a result for both models as of October 22, 2026. Claude Haiku 4.5's coding index rests on 4 independent benchmarks and Qwen3 30B A3B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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