Model comparison
Claude Haiku 4.5 vs Qwen3 Coder Next
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 34.3 on the Noometry Index. Qwen3 Coder Next costs 6.9× less per token, which makes it the better buy when Claude Haiku 4.5's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 1 category and Qwen3 Coder Next in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude Haiku 4.5 leads 44.0 to 36.3.
- The biggest single-benchmark swing is WeirdML: 45.4% for Claude Haiku 4.5 and 34.4% for Qwen3 Coder Next.
- Qwen3 Coder Next is cheaper at $0.12 / $0.80 per million input/output tokens, against $1 / $5 for Claude Haiku 4.5.
- Qwen3 Coder Next accepts more context: 262K tokens versus 200K.
- Qwen3 Coder Next has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | Qwen3 Coder Next | |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 39.5 | 34.3 |
| Released | 2025-10-15 | 2026-02-02 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 64K | 66K |
| Input $ / M tokens | $1 | $0.12 |
| Output $ / M tokens | $5 | $0.80 |
| Results tracked | 53 | 3 |
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Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.0 (#78), Qwen3 Coder Next: 36.3 (#210)
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| SciCode | 43.3% | 32.3% |
| WeirdML | 45.4% | 34.4% |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| LMArena Coding | 1453 | — |
| ALE-Bench | 653.48 | — |
Agentic & Tool Use Not comparable
Claude Haiku 4.5: 33.6 (#52), Qwen3 Coder Next: —
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| Terminal-Bench | 35.5% | — |
| Berkeley Function Calling Leaderboard | 68.7% | — |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| Vending-Bench 2 | 458.89 | — |
Reasoning Qwen3 Coder Next leads
Claude Haiku 4.5: 15.1 (#320), Qwen3 Coder Next: 22.4 (#196)
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| CritPt | 0% | 0% |
| ARC-AGI-2 | 4% | — |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| Chess Puzzles | 8% | — |
| LMArena Hard Prompts | 1420 | — |
| DTBench | 73.6% | — |
| LMCA | 30.9% | — |
| Epoch Capabilities Index | 142.41 | — |
| ForecastBench | 61.4 | — |
Math Not comparable
Claude Haiku 4.5: 44.9 (#78), Qwen3 Coder Next: —
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.7% | — |
| Omni-MATH | 56.1% | — |
| LMArena Math | 1396 | — |
| MATH Level 5 | 96.4% | — |
| FrontierMath (Feb 2025 set) | 5.9% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Not comparable
Claude Haiku 4.5: 37.7 (#153), Qwen3 Coder Next: —
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| GPQA Diamond | 71.2% | — |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| Vectara Hallucination Rate | 9.8% | — |
| GPQA (HELM) | 60.5% | — |
| LMArena Expert | 1442 | — |
Multimodal Not comparable
Claude Haiku 4.5: 26.8 (#118), Qwen3 Coder Next: —
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
Multilingual Not comparable
Claude Haiku 4.5: 49.9 (#129), Qwen3 Coder Next: —
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| LMArena Non-English | 1377 | — |
| LMArena Chinese | 1417 | — |
| LMArena French | 1408 | — |
| LMArena German | 1375 | — |
| LMArena Japanese | 1339 | — |
| LMArena Korean | 1347 | — |
| LMArena Russian | 1381 | — |
| LMArena Spanish | 1420 | — |
Instruction Following Not comparable
Claude Haiku 4.5: 71.4 (#149), Qwen3 Coder Next: —
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| IFEval | 80.1% | — |
| LMArena Instruction Following | 1414 | — |
Long Context Not comparable
Claude Haiku 4.5: 43.6 (#92), Qwen3 Coder Next: —
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| LMArena Longer Query | 1427 | — |
Writing & Preference Not comparable
Claude Haiku 4.5: 57.9 (#123), Qwen3 Coder Next: —
| Benchmark | Claude Haiku 4.5 | Qwen3 Coder Next |
|---|---|---|
| LMArena Text | 1396 | — |
| LMArena Creative Writing | 1372 | — |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |
| LMArena Multi-Turn | 1409 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than Qwen3 Coder Next?
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 34.3 on the Noometry Index. Qwen3 Coder Next costs 6.9× less per token, which makes it the better buy when Claude Haiku 4.5's lead doesn't matter for your workload.
Which is cheaper, Claude Haiku 4.5 or Qwen3 Coder Next?
Qwen3 Coder Next is cheaper. It lists at $0.12 per million input tokens and $0.80 per million output tokens; Claude Haiku 4.5 lists at $1 and $5.
Is Claude Haiku 4.5 or Qwen3 Coder Next better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 36.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3 Coder Next does, with 262K tokens against 200K.
How many benchmarks do Claude Haiku 4.5 and Qwen3 Coder Next share?
3 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Qwen3 Coder Next has 3.