Model comparison
GPT-5.6 Sol 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: GPT-5.6 Sol #3 (Supported); Qwen2.5 Coder 32B Instruct #186 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Qwen2.5 Coder 32B Instruct share 4 comparable benchmark results. 0 of 8 categories are comparable. 42 results are unique to GPT-5.6 Sol; 0 to Qwen2.5 Coder 32B Instruct.
Updated July 23, 2026- Shared results
- 4
- GPT-5.6 Sol only
- 42
- Qwen2.5 Coder 32B Instruct only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.6 Sol 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.
GPT-5.6 Sol is priced at $5.00 input / $30.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen2.5 Coder 32B Instruct. GPT-5.6 Sol 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 | GPT-5.6 Sol | Δ | Qwen2.5 Coder 32B Instruct |
|---|---|---|---|
| Agentic | GPT-5.6 Sol92.0 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
| Coding | GPT-5.6 Sol64.6 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
| Knowledge | GPT-5.6 Sol94.6 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
| Math | GPT-5.6 Sol87.5 | MarginNo overlap | Qwen2.5 Coder 32B InstructNot measured |
| Multimodal | GPT-5.6 Sol83.0 | 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 | GPT-5.6 Sol | Qwen2.5 Coder 32B Instruct | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 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 | GPT-5.6 SolNot available | Qwen2.5 Coder 32B InstructNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Qwen2.5 Coder 32B InstructNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Qwen2.5 Coder 32B Instruct128K | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen2.5 Coder 32B Instruct | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | — | Not comparable |
| BrowseCompSource | 92.2% | — | Not comparable |
| OSWorld 2.0Source | 62.6% | — | Not comparable |
| CyberGymSource | 84.5% | — | Not comparable |
| ExploitGymSource | 33.7% | — | Not comparable |
| ToolathlonSource | 58% | — | Not comparable |
| AA Agentic IndexSource | 54.0% | — | Not comparable |
| τ²-bench resultsSource | 85.1% | — | Not comparable |
| GDPval-AASource | 61.8% | — | Not comparable |
| GDPval-AASource | 1736 | — | Not comparable |
| AA BriefcaseSource | 1501 | — | Not comparable |
| AA ITBenchSource | 56.2% | — | Not comparable |
| AA Tau3 BankingSource | 33.0% | — | Not comparable |
| AA AutomationBenchSource | 51.2% | — | Not comparable |
| AA Harvey LABSource | 87.2% | — | Not comparable |
| terminalBenchHardSource | 65.9% | — | Not comparable |
| aaTerminalBench21Source | 88% | — | Not comparable |
Coding8 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen2.5 Coder 32B Instruct | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | — | Not comparable |
| Terminal-Bench 2.0Source | 91.9% | — | Not comparable |
| deepSweSource | 72.7% | — | Not comparable |
| FrontierCode 1.1 ExtendedSource | 60.6% | — | Not comparable |
| cursorBench32Source | 67.2% | — | Not comparable |
| VulcanBench v3Source | 87.0% | — | Not comparable |
| AA Coding IndexSource | 77.4% | — | Not comparable |
| AA-SciCodeSource | 56.1% | 27.1% | GPT-5.6 Sol leads |
Reasoning4 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen2.5 Coder 32B Instruct | Result |
|---|---|---|---|
| GPQASource | 94.6% | — | Not comparable |
| GPQA-DSource | 94.6% | — | Not comparable |
| HealthBench ProfessionalSource | 60.5% | — | Not comparable |
| HealthBench HardSource | 33.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 58.9% | 7.1% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 94.1% | 41.7% | GPT-5.6 Sol leads |
| AA-HLESource | 47.2% | 3.8% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | 21.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 58.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 88.8% | — | Not comparable |
Math3 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen2.5 Coder 32B Instruct | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.7% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5.6 Sol 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 GPT-5.6 Sol and Qwen2.5 Coder 32B Instruct today?
GPT-5.6 Sol: $5.00 input / $30.00 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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