Model comparison
Claude Opus 4.7 (Adaptive) vs Qwen2.5 Coder 32B Instruct
Head-to-head evidence from 4 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); Qwen2.5 Coder 32B Instruct #186 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 (Adaptive) and Qwen2.5 Coder 32B Instruct share 4 comparable benchmark results. 0 of 8 categories are comparable. 34 results are unique to Claude Opus 4.7 (Adaptive); 0 to Qwen2.5 Coder 32B Instruct.
Updated July 23, 2026- Shared results
- 4
- Claude Opus 4.7 (Adaptive) only
- 34
- Qwen2.5 Coder 32B Instruct only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Claude Opus 4.7 (Adaptive) and Qwen2.5 Coder 32B Instruct is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 2 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Claude Opus 4.7 (Adaptive) is priced at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen2.5 Coder 32B Instruct. Claude Opus 4.7 (Adaptive) has the larger context window at 1M, compared with 128K for Qwen2.5 Coder 32B Instruct.
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 Opus 4.7 (Adaptive) | Δ | Qwen2.5 Coder 32B Instruct |
|---|---|---|---|
| Agentic | Claude Opus 4.7 (Adaptive)75.1 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
| Coding | Claude Opus 4.7 (Adaptive)78.6 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
| Reasoning | Claude Opus 4.7 (Adaptive)75.8 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
| Knowledge | Claude Opus 4.7 (Adaptive)60.0 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
| Multimodal | Claude Opus 4.7 (Adaptive)65.1 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 (Adaptive) | Qwen2.5 Coder 32B Instruct | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7 (Adaptive)$5 input / $25 output | Qwen2.5 Coder 32B Instruct$0 input / $0 output | Qwen2.5 Coder 32B Instruct has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7 (Adaptive)Not available | Qwen2.5 Coder 32B InstructNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7 (Adaptive)Not available | Qwen2.5 Coder 32B InstructNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.7 (Adaptive)1M | Qwen2.5 Coder 32B Instruct128K | Claude Opus 4.7 (Adaptive) lists the larger context window. |
Benchmark Deep Dive
Agentic12 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Qwen2.5 Coder 32B Instruct | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 69.4% | — | Not comparable |
| BrowseCompSource | 79.3% | — | Not comparable |
| MCP AtlasSource | 77.3% | — | Not comparable |
| OSWorld-VerifiedSource | 78% | — | Not comparable |
| CyberGymSource | 73.1% | — | Not comparable |
| AA Agentic IndexSource | 44.4% | — | Not comparable |
| τ²-bench resultsSource | 88.6% | — | Not comparable |
| GDPval-AASource | 49.8% | — | Not comparable |
| GDPval-AASource | 1495 | — | Not comparable |
| OSWorld 2.0Source | 18.2% | — | Not comparable |
| JobBenchSource | 45.9% | — | Not comparable |
| AA ITBenchSource | 46.7% | — | Not comparable |
Coding5 benchmarks
Reasoning4 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Qwen2.5 Coder 32B Instruct | Result |
|---|---|---|---|
| GPQASource | 94.2% | — | Not comparable |
| GPQA-DSource | 94.2% | — | Not comparable |
| HLESource | 54.7% | — | Not comparable |
| HLE w/o toolsSource | 46.9% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 53.5% | 7.1% | Claude Opus 4.7 (Adaptive) leads |
| AA-GPQA DiamondSource | 91.4% | 41.7% | Claude Opus 4.7 (Adaptive) leads |
| AA-HLESource | 39.6% | 3.8% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience IndexSource | 26.2% | — | Not comparable |
| AA-Omniscience AccuracySource | 45.8% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 36.2% | — | Not comparable |
Math1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Qwen2.5 Coder 32B Instruct | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 43.8% | — | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Qwen2.5 Coder 32B Instruct | Result |
|---|---|---|---|
| AA-IFBenchSource | 58.6% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Claude Opus 4.7 (Adaptive) and Qwen2.5 Coder 32B Instruct on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Claude Opus 4.7 (Adaptive) and Qwen2.5 Coder 32B Instruct today?
Claude Opus 4.7 (Adaptive): $5.00 input / $25.00 output per 1M tokens Qwen2.5 Coder 32B Instruct: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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