Model comparison
o3-pro vs Qwen3.5 397B
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: o3-pro #127 (Supported); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. o3-pro and Qwen3.5 397B share 2 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to o3-pro; 53 to Qwen3.5 397B.
Updated July 20, 2026- Shared results
- 2
- o3-pro only
- 0
- Qwen3.5 397B only
- 53
- Comparable categories
- 0 / 8
Benchmark data for o3-pro and Qwen3.5 397B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 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.
o3-pro is priced at $20.00 input / $80.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. o3-pro has the larger context window at 200K, compared with 128K for Qwen3.5 397B.
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 | o3-pro | Δ | Qwen3.5 397B |
|---|---|---|---|
| Agentic | o3-proNot measured | MarginNo overlap | Qwen3.5 397B56.5 |
| Coding | o3-proNot measured | MarginNo overlap | Qwen3.5 397B66.5 |
| Reasoning | o3-proNot measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Knowledge | o3-proNot measured | MarginNo overlap | Qwen3.5 397B56.6 |
| Math | o3-proNot measured | MarginNo overlap | Qwen3.5 397B90.6 |
| Multilingual | o3-proNot measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Multimodal | o3-proNot measured | MarginNo overlap | Qwen3.5 397B79.6 |
| Inst. Following | o3-proNot measured | MarginNo overlap | Qwen3.5 397B92.6 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | o3-pro | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | o3-pro$20 input / $80 output | Qwen3.5 397B$0.6 input / $3.6 output | Qwen3.5 397B has the lower combined listed price. |
| Generation speedtokens per second | o3-pro27 tok/s | Qwen3.5 397B96 tok/s | Qwen3.5 397B has the higher measured throughput. |
| First-answer latencyseconds to first token | o3-pro84.93 s | Qwen3.5 397B2.44 s | Qwen3.5 397B reaches the first token sooner. |
| Context windowmaximum listed tokens | o3-pro200K | Qwen3.5 397B128K | o3-pro lists the larger context window. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | o3-pro | Qwen3.5 397B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 52.5% | Not comparable |
| BrowseCompSource | — | 62% | Not comparable |
| Claw-EvalSource | — | 56.8% | Not comparable |
| QwenClawBenchSource | — | 51.8% | Not comparable |
| τ³-bench resultsSource | — | 68.4% | Not comparable |
| VITA-BenchSource | — | 43.7% | Not comparable |
| DeepPlanningSource | — | 37.6% | Not comparable |
| ToolathlonSource | — | 36.3% | Not comparable |
| MCP AtlasSource | — | 46.1% | Not comparable |
| MCP-TasksSource | — | 74.2% | Not comparable |
| WideResearchSource | — | 74.0% | Not comparable |
| τ²-bench resultsSource | — | 95.6% | Not comparable |
| Gert LabsSource | — | 46.76% | Not comparable |
| ResearchClawBenchSource | — | 14.2% | Not comparable |
| AA Agentic IndexSource | — | 19.9% | Not comparable |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
| GDPval-AASource | — | 23.1% | Not comparable |
| GDPval-AASource | — | 962 | Not comparable |
Coding5 benchmarks
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | o3-pro | Qwen3.5 397B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 32.5% | 33.7% | Qwen3.5 397B leads |
| AA-GPQA DiamondSource | 84.5% | 89.3% | Qwen3.5 397B leads |
| GPQASource | — | 88.4% | Not comparable |
| SuperGPQASource | — | 70.4% | Not comparable |
| MMLU-ProSource | — | 87.8% | Not comparable |
| MMLU-ReduxSource | — | 94.9% | Not comparable |
| C-EvalSource | — | 93% | Not comparable |
| HLESource | — | 28.7% | Not comparable |
| AA-HLESource | — | 27.3% | Not comparable |
| AA-Omniscience IndexSource | — | -29.8% | Not comparable |
| AA-Omniscience AccuracySource | — | 31.4% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 89.1% | Not comparable |
Math5 benchmarks
Multilingual2 benchmarks
Multimodal7 benchmarks
Frequently Asked Questions (3)
Can I compare o3-pro and Qwen3.5 397B 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 o3-pro and Qwen3.5 397B today?
o3-pro: $20.00 input / $80.00 output per 1M tokens Qwen3.5 397B: $0.60 input / $3.60 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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