Claude Haiku 4.5 vs Qwen3 Next 80B A3B Instruct
Claude Haiku 4.5 leads Qwen3 Next 80B A3B Instruct on the Artificial Analysis Intelligence Index, 16.9 to 9.6, and Qwen3 Next 80B A3B Instruct costs 4.5x less per output token ($1.10 vs $5.00 per million). Updated October 22, 2026; 29 benchmarks have a result for both.
Claude Haiku 4.5 or Qwen3 Next 80B A3B Instruct: which to pick
Only Claude Haiku 4.5 has a coding score, 35.6 on the Vibe Coding Index; Qwen3 Next 80B A3B Instruct has none, so the two cannot be ranked on coding.
Pick Qwen3 Next 80B A3B Instruct for output tokens 4.5x cheaper ($1.10 vs $5.00 per million) and a larger context window (262K against 200K tokens).
- Shared results
- 29
- Claude Haiku 4.5 only
- 69
- Qwen3 Next 80B A3B Instruct only
- 12
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Claude Haiku 4.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Claude Haiku 4.5
Claude Haiku 4.5 leads, 16.9 against 9.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Claude Haiku 4.5 has a AA Agentic Index result, 8.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Claude Haiku 4.5 has a GPQA Diamond result, 72.2%.
Directional only
Math
AIME
No call
Only Claude Haiku 4.5 has a AIME result, 82.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Claude Haiku 4.5 has a MMLU Pro result, 78.7%.
Directional only
Web design
Design Arena: websites
No call
Only Claude Haiku 4.5 has a Design Arena: websites result, 1122.
Directional only
Long documents
Listed context window
Qwen3 Next 80B A3B Instruct
Qwen3 Next 80B A3B Instruct takes 262K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Next 80B A3B Instruct
Claude Haiku 4.5 $0.0035, Qwen3 Next 80B A3B Instruct $0.0006 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Claude Haiku 4.5 has the number, $0.56.
Directional only
At a glance
- Coding index
- Claude Haiku 4.5 35.6 from 4 benchmarks, Qwen3 Next 80B A3B Instruct not benchmarked.
- Widest category
- Intelligence, 7.3 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena Text: medicine and healthcare: Claude Haiku 4.5 1394 against Qwen3 Next 80B A3B Instruct 1455, 10.2 points apart on a 0 to 100 scale.
- Output price
- Claude Haiku 4.5 $5.00 against Qwen3 Next 80B A3B Instruct $1.10 per million output tokens, 4.5x apart.
- Context window
- Claude Haiku 4.5 takes 200K tokens, Qwen3 Next 80B 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.
| Category | Claude Haiku 4.5 | Bars | Qwen3 Next 80B A3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 1 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 5 | 12 | ||
| All shared boards | 9 | 20 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| SWE-bench Verified | 66.6% | Not measured | Only Claude Haiku 4.5 measured |
| SWE-bench Multilingual | 64.7% | Not measured | Only Claude Haiku 4.5 measured |
| LiveBench coding | 48.1% | Not measured | Only Claude Haiku 4.5 measured |
| LMArena WebDev | 1330 | Not measured | Only Claude Haiku 4.5 measured |
| AA Coding Index | 43.9 | Not measured | Only Claude Haiku 4.5 measured |
| LiveCodeBench (Vals AI) | 41.2% | Not measured | Only Claude Haiku 4.5 measured |
| SWE-bench Verified (Vals AI) | 66.6% | Not measured | Only Claude Haiku 4.5 measured |
| Vibe Code Bench (Vals AI) | 11.4% | Not measured | Only Claude Haiku 4.5 measured |
| Code migration (Vals AI) | 7.5% | Not measured | Only Claude Haiku 4.5 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Claude Haiku 4.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 43.8% | Not measured | Only Claude Haiku 4.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.4% | Only Qwen3 Next 80B A3B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 9.8% | Only Qwen3 Next 80B A3B Instruct measured |
| Terminal-Bench | 35.5% | Not measured | Only Claude Haiku 4.5 measured |
| WeirdML | 45.4% | Not measured | Only Claude Haiku 4.5 measured |
| LMArena Text: coding | 1454 | 1440 | Claude Haiku 4.5 |
| LMArena Text: software and IT | 1439 | 1447 | Qwen3 Next 80B A3B Instruct |
| LMArena WebDev: React | 1326 | Not measured | Only Claude Haiku 4.5 measured |
| LMArena WebDev: HTML | 1318 | Not measured | Only Claude Haiku 4.5 measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.9 | 9.6 | Claude Haiku 4.5 |
| Epoch Capabilities Index | 142.2 | Not measured | Only Claude Haiku 4.5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| AA Agentic Index | 8.0 | Not measured | Only Claude Haiku 4.5 measured |
| LiveBench research | 42.2% | Not measured | Only Claude Haiku 4.5 measured |
| LiveBench browser | 40.0% | Not measured | Only Claude Haiku 4.5 measured |
| LiveBench long agentic | 11.1% | Not measured | Only Claude Haiku 4.5 measured |
| Finance Agent (Vals AI) | 31.0% | Not measured | Only Claude Haiku 4.5 measured |
| Tax Agent Bench (Vals AI) | 5.9% | Not measured | Only Claude Haiku 4.5 measured |
| Legal Research Bench (Vals AI) | 10.6% | Not measured | Only Claude Haiku 4.5 measured |
| Excel Modeling Benchmark (Vals AI) | 22.7% | Not measured | Only Claude Haiku 4.5 measured |
| τ²-Bench Telecom | Not measured | 41.5% | Only Qwen3 Next 80B A3B Instruct measured |
| BALROG | 31.2% | Not measured | Only Claude Haiku 4.5 measured |
| DeepResearch Bench | 45.5% | Not measured | Only Claude Haiku 4.5 measured |
| Vending-Bench 2 | $459 | Not measured | Only Claude Haiku 4.5 measured |
| Berkeley Function Calling Leaderboard (BFCL) | 68.7% | Not measured | Only Claude Haiku 4.5 measured |
| MCP Atlas | 40.2% | Not measured | Only 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 index21
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 72.2% | Not measured | Only Claude Haiku 4.5 measured |
| LiveBench reasoning | 61.7% | Not measured | Only Claude Haiku 4.5 measured |
| MMMU Pro (Vals AI) | 46.1% | Not measured | Only Claude Haiku 4.5 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 75.9% | Only Qwen3 Next 80B A3B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 12.6% | Only Qwen3 Next 80B A3B Instruct measured |
| GPQA Diamond (Epoch AI run) | 71.2% | Not measured | Only Claude Haiku 4.5 measured |
| ARC-AGI | 47.7% | Not measured | Only Claude Haiku 4.5 measured |
| ARC-AGI-2 | 4.0% | Not measured | Only Claude Haiku 4.5 measured |
| Chess puzzles | 8.0% | Not measured | Only Claude Haiku 4.5 measured |
| LMArena Text: hard prompts | 1421 | 1428 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: expert | 1443 | 1417 | Claude Haiku 4.5 |
| LMArena Text: hard prompts in English | 1435 | 1431 | Claude Haiku 4.5 |
| Kagi LLM Benchmark | Not measured | 66.7% | Only Qwen3 Next 80B A3B Instruct measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| AIME | 82.7% | Not measured | Only Claude Haiku 4.5 measured |
| MGSM (Vals AI) | 92.2% | Not measured | Only Claude Haiku 4.5 measured |
| AA Math Index | Not measured | 84.3 | Only Qwen3 Next 80B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 84.3% | Only Qwen3 Next 80B A3B Instruct measured |
| OTIS Mock AIME | 66.7% | Not measured | Only Claude Haiku 4.5 measured |
| MATH level 5 | 96.4% | Not measured | Only Claude Haiku 4.5 measured |
| LMArena Text: math | 1398 | 1440 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: mathematical work | 1430 | 1434 | Qwen3 Next 80B A3B Instruct |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 78.7% | Not measured | Only Claude Haiku 4.5 measured |
| LegalBench (Vals AI) | 81.2% | Not measured | Only Claude Haiku 4.5 measured |
| CaseLaw (Vals AI) | 56.5% | Not measured | Only Claude Haiku 4.5 measured |
| CorpFin (Vals AI) | 60.6% | Not measured | Only Claude Haiku 4.5 measured |
| TaxEval (Vals AI) | 67.5% | Not measured | Only Claude Haiku 4.5 measured |
| MortgageTax (Vals AI) | 62.2% | Not measured | Only Claude Haiku 4.5 measured |
| MedQA (Vals AI) | 79.6% | Not measured | Only Claude Haiku 4.5 measured |
| MedCode (Vals AI) | 32.7% | Not measured | Only Claude Haiku 4.5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 82.4% | Only Qwen3 Next 80B A3B Instruct measured |
| SimpleQA Verified | 13.2% | Not measured | Only Claude Haiku 4.5 measured |
| LMArena Text: science | 1406 | 1434 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: medicine and healthcare | 1394 | 1455 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: legal and government | 1400 | 1431 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: business and finance | 1400 | 1422 | Qwen3 Next 80B A3B Instruct |
| 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
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1122 | Not measured | Only Claude Haiku 4.5 measured |
| Design Arena: UI components | 1097 | Not measured | Only Claude Haiku 4.5 measured |
| Design Arena: game dev | 1096 | Not measured | Only Claude Haiku 4.5 measured |
| Design Arena: data viz | 1124 | Not measured | Only Claude Haiku 4.5 measured |
| Design Arena: 3D | 1071 | Not measured | Only Claude Haiku 4.5 measured |
| Design Arena: all code categories | 1114 | Not measured | Only Claude Haiku 4.5 measured |
| Design Arena: SVG | 1025 | Not measured | Only Claude Haiku 4.5 measured |
| Design Arena: ASCII art | 1140 | Not measured | Only Claude Haiku 4.5 measured |
| LiveBench design | 59.9% | Not measured | Only Claude Haiku 4.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index512
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| LiveBench data analysis | 59.3% | Not measured | Only Claude Haiku 4.5 measured |
| Public Benefits Bench (Vals AI) | 54.3% | Not measured | Only Claude Haiku 4.5 measured |
| SAGE (Vals AI) | 31.8% | Not measured | Only Claude Haiku 4.5 measured |
| MedScribe (Vals AI) | 85.2% | Not measured | Only Claude Haiku 4.5 measured |
| Vals Multimodal Index | 42.9% | Not measured | Only Claude Haiku 4.5 measured |
| IFBench | Not measured | 60.7% | Only Qwen3 Next 80B A3B Instruct measured |
| Long context reasoning (AA-LCR) | Not measured | 63.7% | Only Qwen3 Next 80B A3B Instruct measured |
| DTBench | 73.6% | Not measured | Only Claude Haiku 4.5 measured |
| LMCA | 30.9% | Not measured | Only Claude Haiku 4.5 measured |
| Fiction.LiveBench | Not measured | 55.6% | Only Qwen3 Next 80B A3B Instruct measured |
| ExploitBench | 13.7% | Not measured | Only Claude Haiku 4.5 measured |
| LMArena Text | 1397 | 1417 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: instruction following | 1414 | 1388 | Claude Haiku 4.5 |
| LMArena Text: creative writing | 1371 | 1333 | Claude Haiku 4.5 |
| LMArena Text: English | 1414 | 1421 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: non-English | 1377 | 1407 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Chinese | 1418 | 1460 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: German | 1374 | 1416 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Japanese | 1338 | 1395 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Korean | 1346 | 1363 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: French | 1411 | 1414 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Spanish | 1421 | 1435 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Russian | 1381 | 1404 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Polish | 1343 | 1398 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: multi-turn | 1409 | 1416 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: longer queries | 1427 | 1402 | Claude Haiku 4.5 |
| LMArena Text: writing and language | 1386 | 1355 | Claude Haiku 4.5 |
| LMArena Text: entertainment and media | 1369 | 1349 | Claude Haiku 4.5 |
| LMArena Document | 1420 | Not measured | Only Claude Haiku 4.5 measured |
| MultiChallenge | 50.5% | Not measured | Only Claude Haiku 4.5 measured |
| EQ-Bench 4 | 1064 | Not measured | Only Claude Haiku 4.5 measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| 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
Qwen3 Next 80B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 Next 80B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 Next 80B 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.
| Specification | Anthropic Claude Haiku 4.5 | Qwen3 Next 80B A3B Instruct |
|---|---|---|
| Maker | Anthropic | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 15, 2025 | September 11, 2025 |
| Context window | 200K | 262K |
| Input $/Mtok | $1.00 | $0.10 |
| Output $/Mtok | $5.00 | $1.10 |
| Coding index | 35.6 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $0.56 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Haiku 4.5 better than Qwen3 Next 80B A3B Instruct for coding?
Only Claude Haiku 4.5 has a coding score, 35.6 on the Vibe Coding Index; Qwen3 Next 80B A3B Instruct has none, so the two cannot be ranked on coding. Pick Qwen3 Next 80B A3B Instruct for output tokens 4.5x cheaper ($1.10 vs $5.00 per million) and a larger context window (262K against 200K tokens).
Which is cheaper, Claude Haiku 4.5 or Qwen3 Next 80B A3B Instruct?
Claude Haiku 4.5 costs $1.00 per million input tokens and $5.00 per million output tokens; Qwen3 Next 80B A3B Instruct costs $0.10 and $1.10. Cost per solved task is known for Claude Haiku 4.5 only.
Which has the bigger context window, Claude Haiku 4.5 or Qwen3 Next 80B A3B Instruct?
Qwen3 Next 80B A3B Instruct, with 262K tokens against 200K.
How many benchmarks is the Claude Haiku 4.5 vs Qwen3 Next 80B A3B Instruct comparison based on?
29 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 Next 80B A3B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.