Model comparison
Claude Haiku 4.5 vs Qwen3.5-35B-A3B
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); Qwen3.5-35B-A3B #72 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Haiku 4.5 and Qwen3.5-35B-A3B share 1 comparable benchmark result. 1 of 8 categories are comparable. 4 results are unique to Claude Haiku 4.5; 27 to Qwen3.5-35B-A3B.
Updated July 23, 2026- Shared results
- 1
- Claude Haiku 4.5 only
- 4
- Qwen3.5-35B-A3B only
- 27
- Comparable categories
- 1 / 8
Pick Qwen3.5-35B-A3B if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.5-35B-A3B has the cleaner BenchAlign overall profile here, landing at 56.97 versus 56.58. 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 Qwen3.5-35B-A3B. That is roughly Infinityx on output cost alone. Qwen3.5-35B-A3B 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. Qwen3.5-35B-A3B 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 | Qwen3.5-35B-A3B |
|---|---|---|---|
| Coding | Claude Haiku 4.573.3 | Margin← 12.7 | Qwen3.5-35B-A3B60.6 |
| Agentic | Claude Haiku 4.5Not measured | MarginNo overlap | Qwen3.5-35B-A3B51.0 |
| Reasoning | Claude Haiku 4.5Not measured | MarginNo overlap | Qwen3.5-35B-A3B59.0 |
| Knowledge | Claude Haiku 4.5Not measured | MarginNo overlap | Qwen3.5-35B-A3B81.6 |
| Math | Claude Haiku 4.54.9 | MarginNo overlap | Qwen3.5-35B-A3BNot measured |
| Multilingual | Claude Haiku 4.5Not measured | MarginNo overlap | Qwen3.5-35B-A3B81.0 |
| Inst. Following | Claude Haiku 4.5Not measured | MarginNo overlap | Qwen3.5-35B-A3B91.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 73.3%B 69.2%Winner: Claude Haiku 4.5Δ 4.1SWE-bench Verified: Claude Haiku 4.5 scored 73.3%; Qwen3.5-35B-A3B scored 69.2%. Claude Haiku 4.5 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 | Qwen3.5-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Haiku 4.5$1 input / $5 output | Qwen3.5-35B-A3B$0 input / $0 output | Qwen3.5-35B-A3B has the lower combined listed price. |
| Generation speedtokens per second | Claude Haiku 4.5Not available | Qwen3.5-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Haiku 4.5Not available | Qwen3.5-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Haiku 4.5200K | Qwen3.5-35B-A3B262K | Qwen3.5-35B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic6 benchmarks
CodingClaude Haiku 4.5 wins3 benchmarks
Reasoning3 benchmarks
Knowledge9 benchmarks
| Benchmark | Claude Haiku 4.5 | Qwen3.5-35B-A3B | Result |
|---|---|---|---|
| MMLU-ProSource | — | 85.3% | Not comparable |
| SuperGPQASource | — | 63.4% | Not comparable |
| GPQASource | — | 84.2% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 29.3% | Not comparable |
| AA-GPQA DiamondSource | — | 84.5% | Not comparable |
| AA-HLESource | — | 19.7% | Not comparable |
| AA-Omniscience IndexSource | — | -46.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 20.5% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 84.0% | Not comparable |
Math2 benchmarks
Multilingual1 benchmarks
| Benchmark | Claude Haiku 4.5 | Qwen3.5-35B-A3B | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 81% | Not comparable |
Multimodal6 benchmarks
Frequently Asked Questions (2)
Which is better, Claude Haiku 4.5 or Qwen3.5-35B-A3B?
Qwen3.5-35B-A3B is ahead on BenchLM's BenchAlign leaderboard, 56.97 to 56.58. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.3% and 69.2%.
Which is better for coding, Claude Haiku 4.5 or Qwen3.5-35B-A3B?
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 73.3 versus 60.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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