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Model comparison

Laguna M.1 vs Qwen3.5 397B

Data verified

Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

Laguna M.1
Poolside
N/A
No comparison
56.19/100
0 category wins2 category wins

Public leaderboard positions: Laguna M.1 unranked (Not scored); Qwen3.5 397B #78 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Laguna M.1 and Qwen3.5 397B share 3 comparable benchmark results. 2 of 8 categories are comparable. 2 results are unique to Laguna M.1; 52 to Qwen3.5 397B.

Updated July 27, 2026
Shared results
3
Laguna M.1 only
2
Qwen3.5 397B only
52
Comparable categories
2 / 8

Treat this as a split decision. Laguna M.1 makes more sense if you need the larger 256K context window or you want the stronger reasoning-first profile; Qwen3.5 397B is the better fit if agentic 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 3 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 M.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.

Laguna M.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 M.1 gives you the larger context window at 256K, 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 scores and score margins for Laguna M.1 and Qwen3.5 397B
CategoryLaguna M.1ΔQwen3.5 397B
AgenticLaguna M.145.8Margin→ 10.7Qwen3.5 397B56.5
CodingLaguna M.164.8Margin→ 1.7Qwen3.5 397B66.5
ReasoningLaguna M.1Not measuredMarginNo overlapQwen3.5 397B63.2
KnowledgeLaguna M.1Not measuredMarginNo overlapQwen3.5 397B56.6
MathLaguna M.1Not measuredMarginNo overlapQwen3.5 397B90.6
MultilingualLaguna M.1Not measuredMarginNo overlapQwen3.5 397B84.7
MultimodalLaguna M.1Not measuredMarginNo overlapQwen3.5 397B79.6
Inst. FollowingLaguna M.1Not measuredMarginNo overlapQwen3.5 397B92.6

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Laguna M.1B · Qwen3.5 397B

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 45.8%B 52.5%
    Winner: Qwen3.5 397BΔ 6.7
    Terminal-Bench 2.0: Laguna M.1 scored 45.8%; Qwen3.5 397B scored 52.5%. Qwen3.5 397B wins this benchmark.

  2. SWE-bench Pro

    Coding
    Source ↗
    A 49.2%B 50.9%
    Winner: Qwen3.5 397BΔ 1.7
    SWE-bench Pro: Laguna M.1 scored 49.2%; Qwen3.5 397B scored 50.9%. Qwen3.5 397B wins this benchmark.

  3. SWE-bench Verified

    Coding
    Source ↗
    A 74.6%B 76.2%
    Winner: Qwen3.5 397BΔ 1.6
    SWE-bench Verified: Laguna M.1 scored 74.6%; Qwen3.5 397B scored 76.2%. Qwen3.5 397B wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricLaguna M.1Qwen3.5 397BComparison
Input / output priceUSD per 1M tokensLaguna M.1Not availableQwen3.5 397B$0.6 input / $3.6 outputA complete price comparison is not available.
Generation speedtokens per secondLaguna M.1Not availableQwen3.5 397B96 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenLaguna M.1Not availableQwen3.5 397B2.44 sA complete latency comparison is not available.
Context windowmaximum listed tokensLaguna M.1256KQwen3.5 397B128KLaguna M.1 lists the larger context window.

Benchmark Deep Dive

AgenticQwen3.5 397B wins
BenchmarkLaguna M.1Qwen3.5 397BResult
Terminal-Bench 2.0Source 45.8%52.5%Qwen3.5 397B leads
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 —962Not comparable
CodingQwen3.5 397B wins
BenchmarkLaguna M.1Qwen3.5 397BResult
SWE-bench VerifiedSource 74.6%76.2%Qwen3.5 397B leads
SWE MultilingualSource 63.1%—Not comparable
SWE-bench ProSource 49.2%50.9%Qwen3.5 397B leads
Terminal-Bench 2.0Source 45.8%—Not comparable
LiveCodeBench v6Source —83.6%Not comparable
AA-SciCodeSource —42.0%Not comparable
AA Coding IndexSource —48.2%Not comparable
Reasoning
BenchmarkLaguna M.1Qwen3.5 397BResult
LongBench v2Source —63.2%Not comparable
AI-NeedleSource —68.7%Not comparable
AA-LCRSource —65.7%Not comparable
CritPtSource —1.7%Not comparable
Knowledge
BenchmarkLaguna M.1Qwen3.5 397BResult
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
Math
BenchmarkLaguna M.1Qwen3.5 397BResult
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
Multilingual
BenchmarkLaguna M.1Qwen3.5 397BResult
MMLU-ProXSource —84.7%Not comparable
NOVA-63Source —59.1%Not comparable
Multimodal
BenchmarkLaguna M.1Qwen3.5 397BResult
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
AA-MMMU-ProSource —77.3%Not comparable
Inst. Following
BenchmarkLaguna M.1Qwen3.5 397BResult
IFEvalSource —92.6%Not comparable
AA-IFBenchSource —78.8%Not comparable
Frequently Asked Questions (3)

Which is better, Laguna M.1 or Qwen3.5 397B?

Laguna M.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 M.1 or Qwen3.5 397B?

Qwen3.5 397B has the edge for coding in this comparison, averaging 66.5 versus 64.8. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Laguna M.1 or Qwen3.5 397B?

Qwen3.5 397B has the edge for agentic tasks in this comparison, averaging 56.5 versus 45.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

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Last updated: July 27, 2026

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