Model comparison
Llama 4 Scout 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: Llama 4 Scout #174 (Supported); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Llama 4 Scout and Qwen3.5 397B share 16 comparable benchmark results. 0 of 8 categories are comparable. 2 results are unique to Llama 4 Scout; 39 to Qwen3.5 397B.
Updated July 20, 2026- Shared results
- 16
- Llama 4 Scout only
- 2
- Qwen3.5 397B only
- 39
- Comparable categories
- 0 / 8
Benchmark data for Llama 4 Scout and Qwen3.5 397B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 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.
Qwen3.5 397B is priced at $0.60 input / $3.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Scout. Llama 4 Scout has the larger context window at 10M, 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 | Llama 4 Scout | Δ | Qwen3.5 397B |
|---|---|---|---|
| Agentic | Llama 4 ScoutNot measured | MarginNo overlap | Qwen3.5 397B56.5 |
| Coding | Llama 4 ScoutNot measured | MarginNo overlap | Qwen3.5 397B66.5 |
| Reasoning | Llama 4 ScoutNot measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Knowledge | Llama 4 ScoutNot measured | MarginNo overlap | Qwen3.5 397B56.6 |
| Math | Llama 4 ScoutNot measured | MarginNo overlap | Qwen3.5 397B90.6 |
| Multilingual | Llama 4 ScoutNot measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Multimodal | Llama 4 ScoutNot measured | MarginNo overlap | Qwen3.5 397B79.6 |
| Inst. Following | Llama 4 ScoutNot 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 | Llama 4 Scout | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Llama 4 Scout$0 input / $0 output | Qwen3.5 397B$0.6 input / $3.6 output | Llama 4 Scout has the lower combined listed price. |
| Generation speedtokens per second | Llama 4 Scout128 tok/s | Qwen3.5 397B96 tok/s | Llama 4 Scout has the higher measured throughput. |
| First-answer latencyseconds to first token | Llama 4 Scout0.70 s | Qwen3.5 397B2.44 s | Llama 4 Scout reaches the first token sooner. |
| Context windowmaximum listed tokens | Llama 4 Scout10M | Qwen3.5 397B128K | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | Llama 4 Scout | Qwen3.5 397B | Result |
|---|---|---|---|
| AA Agentic IndexSource | 1.1% | 19.9% | Qwen3.5 397B leads |
| τ²-bench resultsSource | 15.5% | 95.6% | Qwen3.5 397B leads |
| GDPval-AASource | 0.0% | 23.1% | Qwen3.5 397B leads |
| GDPval-AASource | 90 | 962 | 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 |
| Gert LabsSource | — | 46.76% | Not comparable |
| ResearchClawBenchSource | — | 14.2% | Not comparable |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
Coding5 benchmarks
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | Llama 4 Scout | Qwen3.5 397B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 10.0% | 33.7% | Qwen3.5 397B leads |
| AA-GPQA DiamondSource | 58.7% | 89.3% | Qwen3.5 397B leads |
| AA-HLESource | 4.3% | 27.3% | Qwen3.5 397B leads |
| AA-Omniscience IndexSource | -52.4% | -29.8% | Qwen3.5 397B leads |
| AA-Omniscience AccuracySource | 14.6% | 31.4% | Qwen3.5 397B leads |
| AA-Omniscience Hallucination RateSource | 78.3% | 89.1% | Llama 4 Scout 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 |
Math6 benchmarks
Multilingual2 benchmarks
Multimodal8 benchmarks
| Benchmark | Llama 4 Scout | Qwen3.5 397B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 52.9% | 77.3% | Qwen3.5 397B leads |
| Design Arena WebsiteSource | 783 | — | 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 (3)
Can I compare Llama 4 Scout 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 Llama 4 Scout and Qwen3.5 397B today?
Llama 4 Scout: $0.00 input / $0.00 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.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.