Coding
Like-for-like- Laguna M.1
- 29.7
- Supported · #140/151
- Qwen3.6 Plus
- 46.9
- Supported · #76/151
- Basis
- BenchAlign lane · 6 vs 7 public rows
- Reading
- Qwen3.6 Plus leads · intervals overlap
Laguna M.1 vs Qwen3.6 Plus
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Qwen3.6 Plus has the higher public score, 60.4 versus 3.93, and the 90% score intervals do not overlap.
9 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Coding work
Code generation, repair, and software-engineering tasks
Qwen3.6 Plus
Qwen3.6 Plus leads on the public coding lane, 46.9 to 29.7, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Qwen3.6 Plus
Qwen3.6 Plus has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Laguna M.1 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 Laguna M.1 only
9 Shared
39 Qwen3.6 Plus only
- Shared results
- 9
- Laguna M.1 only
- 1
- Qwen3.6 Plus only
- 39
- Like-for-like categories
- 1 / 8
2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Agentic
Directional only- Laguna M.1
- 23.9
- Estimated · #147/152
- Qwen3.6 Plus
- 36.0
- Supported · #132/152
- Basis
- BenchAlign lane · 2 vs 13 public rows
- Reading
- Directional only
Knowledge
Directional only- Laguna M.1
- 18.6
- Estimated · #182/183
- Qwen3.6 Plus
- 54.0
- Supported · #60/183
- Basis
- BenchAlign lane · 2 vs 8 public rows
- Reading
- Directional only
Reasoning
Not comparable- Laguna M.1
- Not ranked
- Qwen3.6 Plus
- 60.1
- Unranked · 4 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- Laguna M.1
- Not ranked
- Qwen3.6 Plus
- 62.4
- #4/7
- Basis
- Provisional lane · 0 vs 4 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Laguna M.1
- Not ranked
- Qwen3.6 Plus
- 69.7
- #4/12
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Laguna M.1
- Not ranked
- Qwen3.6 Plus
- 66.3
- #22/48
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Laguna M.1
- Not ranked
- Qwen3.6 Plus
- 85.5
- #43/123
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | Laguna M.1 | Qwen3.6 Plus | Basis | Reading |
|---|---|---|---|---|
| Coding | 29.7Supported · #140/151 | 46.9Supported · #76/151 | Like-for-likeBenchAlign lane · 6 vs 7 public rows | Qwen3.6 Plus leads · intervals overlap |
| Agentic | 23.9Estimated · #147/152 | 36.0Supported · #132/152 | Directional onlyBenchAlign lane · 2 vs 13 public rows | Directional only |
| Knowledge | 18.6Estimated · #182/183 | 54.0Supported · #60/183 | Directional onlyBenchAlign lane · 2 vs 8 public rows | Directional only |
| Reasoning | Not ranked | 60.1Unranked · 4 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | Not ranked | 62.4#4/7 | Not comparableProvisional lane · 0 vs 4 weighted rows | Not comparable |
| Multilingual | Not ranked | 69.7#4/12 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | 66.3#22/48 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Instruction following | Not ranked | 85.5#43/123 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
MMLU-Pro (Vals)
Knowledge
LiveCodeBench (Vals)
Coding
Terminal-Bench 2.0
Agentic
SWE Multilingual
Coding
SWE-bench Pro
Coding
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Laguna M.1
- API rate not published
- Fits in one request
- Qwen3.6 Plus
- API rate not published
- Fits in one request
Laguna M.1 has no comparable published API token rate. Qwen3.6 Plus has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Laguna M.1
- API rate not published
- Fits in one request
- Qwen3.6 Plus
- API rate not published
- Fits in one request
Laguna M.1 has no comparable published API token rate. Qwen3.6 Plus has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Laguna M.1
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Qwen3.6 Plus
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Laguna M.1 has no comparable published API token rate. Qwen3.6 Plus has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationLaguna M.1Qwen3.6 Plus
Context window
Maximum documented context; output-token limits may be lower.
Laguna M.1
256K
Qwen3.6 Plus
1M
API model ID
Laguna M.1
Not sourced
Qwen3.6 Plus
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Laguna M.1
No comparable hosted API rate
Qwen3.6 Plus
No comparable hosted API rate
Documented inputs
Laguna M.1
Not sourced
Qwen3.6 Plus
Not sourced
Documented outputs
Laguna M.1
Not sourced
Qwen3.6 Plus
Not sourced
Provider availability
Laguna M.1
Not sourced
Qwen3.6 Plus
Not sourced
Reasoning profile
Laguna M.1
Reasoning
Qwen3.6 Plus
Reasoning
Weight access
Laguna M.1
Proprietary
Qwen3.6 Plus
Proprietary
License
Laguna M.1
Proprietary
Qwen3.6 Plus
Proprietary
Release date
Laguna M.1
2026-04-28
Qwen3.6 Plus
2026-04-02
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- Qwen3.6 Plus has the higher public score, 60.4 versus 3.93, and the 90% score intervals do not overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Qwen3.6 Plus has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence49 rows
Agentic
Terminal-Bench 2.0
Laguna M.145.8%SourceQwen3.6 Plus61.6%SourceQwen3.6 Plus leads this result
Terminal-Bench 2.1 (Vals)
Laguna M.134.1%SourceQwen3.6 Plus53.2%SourceQwen3.6 Plus leads this result
Claw-Eval
Laguna M.1—Qwen3.6 Plus58.8%SourceNot directly comparable
QwenClawBench
Laguna M.1—Qwen3.6 Plus57.2%SourceNot directly comparable
τ³-bench results
Laguna M.1—Qwen3.6 Plus70.7%SourceNot directly comparable
VITA-Bench
Laguna M.1—Qwen3.6 Plus44.3%SourceNot directly comparable
DeepPlanning
Laguna M.1—Qwen3.6 Plus41.5%SourceNot directly comparable
Toolathlon
Laguna M.1—Qwen3.6 Plus39.8%SourceNot directly comparable
MCP Atlas
Laguna M.1—Qwen3.6 Plus48.2%SourceNot directly comparable
MCP-Tasks
Laguna M.1—Qwen3.6 Plus74.1%SourceNot directly comparable
WideResearch
Laguna M.1—Qwen3.6 Plus74.3%SourceNot directly comparable
Gert Labs
Laguna M.1—Qwen3.6 Plus50.60%SourceNot directly comparable
ResearchClawBench
Laguna M.1—Qwen3.6 Plus18.0%SourceNot directly comparable
Coding
SWE-bench Verified
Laguna M.174.6%SourceQwen3.6 Plus78.8%SourceQwen3.6 Plus leads this result
SWE Multilingual
Laguna M.163.1%SourceQwen3.6 Plus73.8%SourceQwen3.6 Plus leads this result
SWE-bench Pro
Laguna M.149.2%SourceQwen3.6 Plus56.6%SourceQwen3.6 Plus leads this result
Terminal-Bench 2.0
Laguna M.145.8%SourceQwen3.6 Plus—Not directly comparable
LiveCodeBench (Vals)
Laguna M.168.1%SourceQwen3.6 Plus86.0%SourceQwen3.6 Plus leads this result
SWE-bench (Vals)
Laguna M.157.6%SourceQwen3.6 Plus73.4%SourceQwen3.6 Plus leads this result
LiveCodeBench v6
Laguna M.1—Qwen3.6 Plus87.1%SourceNot directly comparable
Vibe Code Bench
Laguna M.1—Qwen3.6 Plus25.56%SourceNot directly comparable
Reasoning
Knowledge
GPQA Diamond (Vals)
Laguna M.127.0%SourceQwen3.6 Plus87.4%SourceQwen3.6 Plus leads this result
MMLU-Pro (Vals)
Laguna M.168.8%SourceQwen3.6 Plus87.7%SourceQwen3.6 Plus leads this result
GPQA
Laguna M.1—Qwen3.6 Plus90.4%SourceNot directly comparable
SuperGPQA
Laguna M.1—Qwen3.6 Plus71.6%SourceNot directly comparable
MMLU-Pro
Laguna M.1—Qwen3.6 Plus88.5%SourceNot directly comparable
MMLU-Redux
Laguna M.1—Qwen3.6 Plus94.5%SourceNot directly comparable
C-Eval
Laguna M.1—Qwen3.6 Plus93.3%SourceNot directly comparable
HLE
Laguna M.1—Qwen3.6 Plus28.8%SourceNot directly comparable
Math
AIME26
Laguna M.1—Qwen3.6 Plus95.3%SourceNot directly comparable
HMMT Feb 2025
Laguna M.1—Qwen3.6 Plus96.7%SourceNot directly comparable
HMMT Nov 2025
Laguna M.1—Qwen3.6 Plus94.6%SourceNot directly comparable
HMMT Feb 2026
Laguna M.1—Qwen3.6 Plus87.8%SourceNot directly comparable
MMAnswerBench
Laguna M.1—Qwen3.6 Plus83.8%SourceNot directly comparable
FrontierMath v2 (Tiers 1-3)
Laguna M.1—Qwen3.6 Plus26.207%SourceNot directly comparable
FrontierMath v2 (Tier 4)
Laguna M.1—Qwen3.6 Plus8.333%SourceNot directly comparable
Multilingual
Multimodal
MMMU
Laguna M.1—Qwen3.6 Plus86.0%SourceNot directly comparable
MMMU-Pro
Laguna M.1—Qwen3.6 Plus78.8%SourceNot directly comparable
MathVision
Laguna M.1—Qwen3.6 Plus88.0%SourceNot directly comparable
VideoMMMU
Laguna M.1—Qwen3.6 Plus84.0%SourceNot directly comparable
ScreenSpot Pro
Laguna M.1—Qwen3.6 Plus68.2%SourceNot directly comparable
CharXiv
Laguna M.1—Qwen3.6 Plus81.5%SourceNot directly comparable
V*
Laguna M.1—Qwen3.6 Plus96.9%SourceNot directly comparable
Instruction following
Frequently asked questions
Which is better, Laguna M.1 or Qwen3.6 Plus?
Qwen3.6 Plus has the higher public score, 60.4 versus 3.93, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, Laguna M.1 or Qwen3.6 Plus?
Qwen3.6 Plus leads the public coding lane, 46.9 to 29.7, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Laguna M.1 or Qwen3.6 Plus?
Qwen3.6 Plus scores higher for agentic tasks on the public lane, 36 to 23.9. Laguna M.1 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Laguna M.1 or Qwen3.6 Plus?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Laguna M.1 or Qwen3.6 Plus?
Qwen3.6 Plus has the larger documented context window: 1M, compared with 256K.
Related comparisons
Last updated September 10, 2026
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