Model comparison
Claude Haiku 4.5 vs Qwen3.6-27B
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Haiku 4.5 #77 (Estimated); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Haiku 4.5 and Qwen3.6-27B share 1 comparable benchmark result. 2 of 8 categories are comparable. 4 results are unique to Claude Haiku 4.5; 53 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 1
- Claude Haiku 4.5 only
- 4
- Qwen3.6-27B only
- 53
- Comparable categories
- 2 / 8
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Haiku 4.5 has the cleaner BenchAlign overall profile here, landing at 56.58 versus 53.82. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Claude Haiku 4.5 is also the more expensive model on tokens at $1.00 input / $5.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while Claude Haiku 4.5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Qwen3.6-27B gives you the larger context window at 262K, compared with 200K for Claude Haiku 4.5.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude Haiku 4.5 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | Claude Haiku 4.54.9 | Margin→ 84.3 | Qwen3.6-27B89.2 |
| Coding | Claude Haiku 4.573.3 | Margin→ 4.2 | Qwen3.6-27B77.5 |
| Agentic | Claude Haiku 4.5Not measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Knowledge | Claude Haiku 4.5Not measured | MarginNo overlap | Qwen3.6-27B53.3 |
| Multimodal | Claude Haiku 4.5Not measured | MarginNo overlap | Qwen3.6-27B76.7 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 73.3%B 77.2%Winner: Qwen3.6-27BΔ 3.9SWE-bench Verified: Claude Haiku 4.5 scored 73.3%; Qwen3.6-27B scored 77.2%. Qwen3.6-27B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Haiku 4.5 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Haiku 4.5$1 input / $5 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | Claude Haiku 4.5Not available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Haiku 4.5Not available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Haiku 4.5200K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | Claude Haiku 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| JobBenchSource | 16.0% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| AA Agentic IndexSource | — | 27.0% | Not comparable |
| τ²-bench resultsSource | — | 94.2% | Not comparable |
| GDPval-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 1140 | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
CodingQwen3.6-27B wins8 benchmarks
| Benchmark | Claude Haiku 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.3% | 77.2% | Qwen3.6-27B leads |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
| AA Coding IndexSource | — | 53.7% | Not comparable |
| AA-SciCodeSource | — | 39.8% | Not comparable |
Reasoning2 benchmarks
Knowledge12 benchmarks
| Benchmark | Claude Haiku 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 37.0% | Not comparable |
| AA-GPQA DiamondSource | — | 84.2% | Not comparable |
| AA-HLESource | — | 21.6% | Not comparable |
| AA-Omniscience IndexSource | — | -19.8% | Not comparable |
| AA-Omniscience AccuracySource | — | 19.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 48.3% | Not comparable |
MathQwen3.6-27B wins7 benchmarks
| Benchmark | Claude Haiku 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 5.903% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 2.083% | — | Not comparable |
| HMMT Feb 2025Source | — | 93.8% | Not comparable |
| HMMT Nov 2025Source | — | 90.7% | Not comparable |
| HMMT Feb 2026Source | — | 84.3% | Not comparable |
| MMAnswerBenchSource | — | 80.8% | Not comparable |
| AIME26Source | — | 94.1% | Not comparable |
Multimodal17 benchmarks
| Benchmark | Claude Haiku 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1152 | — | Not comparable |
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
| AA-MMMU-ProSource | — | 74.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Claude Haiku 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 67.6% | Not comparable |
Frequently Asked Questions (3)
Which is better, Claude Haiku 4.5 or Qwen3.6-27B?
Claude Haiku 4.5 is ahead on BenchLM's BenchAlign leaderboard, 56.58 to 53.82. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.3% and 77.2%.
Which is better for coding, Claude Haiku 4.5 or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 73.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, Claude Haiku 4.5 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 4.9. Claude Haiku 4.5 stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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