Model comparison
GPT-4.1 vs Qwen3.5 397B
Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-4.1 #111 (Supported); Qwen3.5 397B #77 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 and Qwen3.5 397B share 16 comparable benchmark results. 4 of 8 categories are comparable. 4 results are unique to GPT-4.1; 39 to Qwen3.5 397B.
Updated July 24, 2026- Shared results
- 16
- GPT-4.1 only
- 4
- Qwen3.5 397B only
- 39
- Comparable categories
- 4 / 8
Pick Qwen3.5 397B if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 evidence categories; 4 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 397B is clearly ahead on the BenchAlign aggregate, 56.26 to 50.44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B's sharpest advantage is in mathematics, where it averages 90.6 against 4.1. The single biggest benchmark swing on the page is GPQA, 66.3% to 88.4%. GPT-4.1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. That is roughly 2.2x on output cost alone. GPT-4.1 gives you the larger context window at 1M, 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 | GPT-4.1 | Δ | Qwen3.5 397B |
|---|---|---|---|
| Math | GPT-4.14.1 | Margin→ 86.5 | Qwen3.5 397B90.6 |
| Coding | GPT-4.154.6 | Margin→ 11.9 | Qwen3.5 397B66.5 |
| Knowledge | GPT-4.166.3 | Margin← 9.7 | Qwen3.5 397B56.6 |
| Inst. Following | GPT-4.187.4 | Margin→ 5.2 | Qwen3.5 397B92.6 |
| Agentic | GPT-4.1Not measured | MarginNo overlap | Qwen3.5 397B56.5 |
| Reasoning | GPT-4.1Not measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Multilingual | GPT-4.1Not measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Multimodal | GPT-4.1Not measured | MarginNo overlap | Qwen3.5 397B79.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 66.3%B 88.4%Winner: Qwen3.5 397BΔ 22.1GPQA: GPT-4.1 scored 66.3%; Qwen3.5 397B scored 88.4%. Qwen3.5 397B wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 54.6%B 76.2%Winner: Qwen3.5 397BΔ 21.6SWE-bench Verified: GPT-4.1 scored 54.6%; Qwen3.5 397B scored 76.2%. Qwen3.5 397B wins this benchmark. - Source ↗
IFEval
Inst. FollowingA 87.4%B 92.6%Winner: Qwen3.5 397BΔ 5.2IFEval: GPT-4.1 scored 87.4%; Qwen3.5 397B scored 92.6%. Qwen3.5 397B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1$2 input / $8 output | Qwen3.5 397B$0.6 input / $3.6 output | Qwen3.5 397B has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1108 tok/s | Qwen3.5 397B96 tok/s | GPT-4.1 has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-4.11.02 s | Qwen3.5 397B2.44 s | GPT-4.1 reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-4.11M | Qwen3.5 397B128K | GPT-4.1 lists the larger context window. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | GPT-4.1 | Qwen3.5 397B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 47.1% | 95.6% | Qwen3.5 397B leads |
| Gert LabsSource | 25.65% | 46.76% | Qwen3.5 397B leads |
| 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 |
| 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 |
CodingQwen3.5 397B wins5 benchmarks
Reasoning4 benchmarks
KnowledgeGPT-4.1 wins13 benchmarks
| Benchmark | GPT-4.1 | Qwen3.5 397B | Result |
|---|---|---|---|
| MMLUSource | 90.2% | — | Not comparable |
| GPQASource | 66.3% | 88.4% | Qwen3.5 397B leads |
| Artificial Analysis Intelligence IndexSource | 19.4% | 33.7% | Qwen3.5 397B leads |
| AA-GPQA DiamondSource | 66.6% | 89.3% | Qwen3.5 397B leads |
| AA-HLESource | 4.6% | 27.3% | Qwen3.5 397B leads |
| AA-Omniscience IndexSource | -36.2% | -29.8% | Qwen3.5 397B leads |
| AA-Omniscience AccuracySource | 24.2% | 31.4% | Qwen3.5 397B leads |
| AA-Omniscience Hallucination RateSource | 79.6% | 89.1% | GPT-4.1 leads |
| 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 |
MathQwen3.5 397B wins7 benchmarks
| Benchmark | GPT-4.1 | Qwen3.5 397B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 5.517% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 0.000% | — | Not comparable |
| AIME26Source | — | 93.3% | Not comparable |
| HMMT Feb 2025Source | — | 94.8% | Not comparable |
| HMMT Nov 2025Source | — | 92.7% | Not comparable |
| HMMT Feb 2026Source | — | 87.9% | Not comparable |
| MMAnswerBenchSource | — | 80.9% | Not comparable |
Multilingual2 benchmarks
Multimodal8 benchmarks
| Benchmark | GPT-4.1 | Qwen3.5 397B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 61.2% | 77.3% | Qwen3.5 397B leads |
| Design Arena WebsiteSource | 1068 | — | Not comparable |
| MMMU-ProSource | — | 79% | Not comparable |
| MathVisionSource | — | 88.6% | Not comparable |
| CharXivSource | — | 80.8% | Not comparable |
| VideoMMMUSource | — | 84.7% | Not comparable |
| ScreenSpot ProSource | — | 65.6% | Not comparable |
| V*Source | — | 95.8% | Not comparable |
Frequently Asked Questions (5)
Which is better, GPT-4.1 or Qwen3.5 397B?
Qwen3.5 397B is ahead on BenchLM's BenchAlign leaderboard, 56.26 to 50.44. The biggest single separator in this matchup is GPQA, where the scores are 66.3% and 88.4%.
Which is better for knowledge tasks, GPT-4.1 or Qwen3.5 397B?
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 66.3 versus 56.6. Inside this category, AA-GPQA Diamond is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-4.1 or Qwen3.5 397B?
Qwen3.5 397B has the edge for coding in this comparison, averaging 66.5 versus 54.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, GPT-4.1 or Qwen3.5 397B?
Qwen3.5 397B has the edge for math in this comparison, averaging 90.6 versus 4.1. GPT-4.1 stays close enough that the answer can still flip depending on your workload.
Which is better for instruction following, GPT-4.1 or Qwen3.5 397B?
Qwen3.5 397B has the edge for instruction following in this comparison, averaging 92.6 versus 87.4. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.