Model comparison
Laguna S 2.1 vs Qwen3.5 397B
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Laguna S 2.1 unranked (Not scored); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Laguna S 2.1 and Qwen3.5 397B share 2 comparable benchmark results. 2 of 8 categories are comparable. 4 results are unique to Laguna S 2.1; 53 to Qwen3.5 397B.
Updated July 21, 2026- Shared results
- 2
- Laguna S 2.1 only
- 4
- Qwen3.5 397B only
- 53
- Comparable categories
- 2 / 8
Treat this as a split decision. Laguna S 2.1 makes more sense if agentic is the priority or you want the cheaper token bill; Qwen3.5 397B is the better fit if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Laguna S 2.1 and Qwen3.5 397B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Qwen3.5 397B is also the more expensive model on tokens at $0.60 input / $3.60 output per 1M tokens, versus $0.10 input / $0.20 output per 1M tokens for Laguna S 2.1. That is roughly 18.0x on output cost alone. Laguna S 2.1 is the reasoning model in the pair, while Qwen3.5 397B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Laguna S 2.1 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 | Laguna S 2.1 | Δ | Qwen3.5 397B |
|---|---|---|---|
| Agentic | Laguna S 2.170.2 | Margin← 13.7 | Qwen3.5 397B56.5 |
| Coding | Laguna S 2.159.4 | Margin→ 7.1 | Qwen3.5 397B66.5 |
| Reasoning | Laguna S 2.1Not measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Knowledge | Laguna S 2.1Not measured | MarginNo overlap | Qwen3.5 397B56.6 |
| Math | Laguna S 2.1Not measured | MarginNo overlap | Qwen3.5 397B90.6 |
| Multilingual | Laguna S 2.1Not measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Multimodal | Laguna S 2.1Not measured | MarginNo overlap | Qwen3.5 397B79.6 |
| Inst. Following | Laguna S 2.1Not measured | MarginNo overlap | Qwen3.5 397B92.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 70.2%B 52.5%Winner: Laguna S 2.1Δ 17.7Terminal-Bench 2.0: Laguna S 2.1 scored 70.2%; Qwen3.5 397B scored 52.5%. Laguna S 2.1 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 59.4%B 50.9%Winner: Laguna S 2.1Δ 8.5SWE-bench Pro: Laguna S 2.1 scored 59.4%; Qwen3.5 397B scored 50.9%. Laguna S 2.1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Laguna S 2.1 | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Laguna S 2.1$0.1 input / $0.2 output | Qwen3.5 397B$0.6 input / $3.6 output | Laguna S 2.1 has the lower combined listed price. |
| Generation speedtokens per second | Laguna S 2.1Not available | Qwen3.5 397B96 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Laguna S 2.1Not available | Qwen3.5 397B2.44 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Laguna S 2.11M | Qwen3.5 397B128K | Laguna S 2.1 lists the larger context window. |
Benchmark Deep Dive
AgenticLaguna S 2.1 wins19 benchmarks
| Benchmark | Laguna S 2.1 | Qwen3.5 397B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 70.2% | 52.5% | Laguna S 2.1 leads |
| Toolathlon-VerifiedSource | 49.7% | — | 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 |
CodingQwen3.5 397B wins8 benchmarks
| Benchmark | Laguna S 2.1 | Qwen3.5 397B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 70.2% | — | Not comparable |
| SWE MultilingualSource | 78.5% | — | Not comparable |
| SWE-bench ProSource | 59.4% | 50.9% | Laguna S 2.1 leads |
| deepSweSource | 40.4% | — | Not comparable |
| SWE-bench VerifiedSource | — | 76.2% | Not comparable |
| LiveCodeBench v6Source | — | 83.6% | Not comparable |
| AA-SciCodeSource | — | 42.0% | Not comparable |
| AA Coding IndexSource | — | 48.2% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | Laguna S 2.1 | Qwen3.5 397B | Result |
|---|---|---|---|
| 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 |
| Artificial Analysis Intelligence IndexSource | — | 33.7% | Not comparable |
| AA-GPQA DiamondSource | — | 89.3% | 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)
Which is better, Laguna S 2.1 or Qwen3.5 397B?
Laguna S 2.1 and Qwen3.5 397B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for coding, Laguna S 2.1 or Qwen3.5 397B?
Qwen3.5 397B has the edge for coding in this comparison, averaging 66.5 versus 59.4. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Laguna S 2.1 or Qwen3.5 397B?
Laguna S 2.1 has the edge for agentic tasks in this comparison, averaging 70.2 versus 56.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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