Agentic
Not comparable- Qwen3.7 Max
- 69.7
- Trinity-Large-Thinking
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Qwen3.7 Max vs Trinity-Large-Thinking
Updated August 18, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Qwen3.7 Max has the higher public score estimate, 71.6 versus 47.88, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
2 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Long documents
Prompts that approach the documented context limit
Qwen3.7 Max
Qwen3.7 Max has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
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: rate-fallback
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.
33 Qwen3.7 Max only
2 Shared
3 Trinity-Large-Thinking only
- Shared results
- 2
- Qwen3.7 Max only
- 33
- Trinity-Large-Thinking only
- 3
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Not comparable- Qwen3.7 Max
- 77.9
- Trinity-Large-Thinking
- Not measured
- Weighted basis
- 4 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Qwen3.7 Max
- 90.4
- Trinity-Large-Thinking
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Qwen3.7 Max
- 64.2
- Trinity-Large-Thinking
- Not measured
- Weighted basis
- 4 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Qwen3.7 Max
- 97.1
- Trinity-Large-Thinking
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Qwen3.7 Max
- 87.0
- Trinity-Large-Thinking
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Qwen3.7 Max
- Not measured
- Trinity-Large-Thinking
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Qwen3.7 Max
- 84.4
- Trinity-Large-Thinking
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
| Category | Qwen3.7 Max | Trinity-Large-Thinking | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 69.7 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Coding | 77.9 | Not measured | Not comparable4 vs 0 rows | Not comparable |
| Reasoning | 90.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Knowledge | 64.2 | Not measured | Not comparable4 vs 0 rows | Not comparable |
| Math | 97.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Multilingual | 87.0 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | 84.4 | Not measured | Not comparable2 vs 0 rows | Not comparable |
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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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
- Qwen3.7 Max
- API rate not published
- Fits in one request
- Trinity-Large-Thinking
- $0.0007
- Fits in one request
Qwen3.7 Max has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Qwen3.7 Max
- API rate not published
- Fits in one request
- Trinity-Large-Thinking
- $0.0152
- Fits in one request
Qwen3.7 Max has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Qwen3.7 Max
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Trinity-Large-Thinking
- $0.064
- Fits in one request
- Cached input priced at the published list-input rate
Trinity-Large-Thinking has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.7 Max 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.
SpecificationQwen3.7 MaxTrinity-Large-Thinking
Context window
Maximum documented context; output-token limits may be lower.
Qwen3.7 Max
1M
Trinity-Large-Thinking
512K
API model ID
Qwen3.7 Max
Not sourced
Trinity-Large-Thinking
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Qwen3.7 Max
No comparable hosted API rate
Trinity-Large-Thinking
Not published
Documented inputs
Qwen3.7 Max
Not sourced
Trinity-Large-Thinking
Not sourced
Documented outputs
Qwen3.7 Max
Not sourced
Trinity-Large-Thinking
Not sourced
Provider availability
Qwen3.7 Max
Not sourced
Trinity-Large-Thinking
Not sourced
Reasoning profile
Qwen3.7 Max
Reasoning
Trinity-Large-Thinking
Reasoning
Weight access
Qwen3.7 Max
Proprietary
Trinity-Large-Thinking
Open Weight
License
Qwen3.7 Max
Proprietary
Trinity-Large-Thinking
Open Weight
Release date
Qwen3.7 Max
2026-05-16
Trinity-Large-Thinking
2026-03-10
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
- Qwen3.7 Max has the higher public score estimate, 71.6 versus 47.88, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Qwen3.7 Max 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 evidence38 rows
Agentic
Terminal-Bench 2.0
Qwen3.7 Max69.7%SourceTrinity-Large-Thinking—Not directly comparable
QwenClawBench
Qwen3.7 Max64.3%SourceTrinity-Large-Thinking—Not directly comparable
Claw-Eval
Qwen3.7 Max65.2%SourceTrinity-Large-Thinking—Not directly comparable
BFCL v4
Qwen3.7 Max75.0%SourceTrinity-Large-Thinking—Not directly comparable
MCP Atlas
Qwen3.7 Max76.4%SourceTrinity-Large-Thinking—Not directly comparable
VITA-Bench
Qwen3.7 Max47.9%SourceTrinity-Large-Thinking—Not directly comparable
HLE w/ tools
Qwen3.7 Max53.5%SourceTrinity-Large-Thinking—Not directly comparable
Gert Labs
Shared sourceQwen3.7 Max64.27%Trinity-Large-Thinking32.55%Qwen3.7 Max leads this result
ResearchClawBench
Qwen3.7 Max18.7%SourceTrinity-Large-Thinking—Not directly comparable
Coding
SWE-bench Verified
Qwen3.7 Max80.4%SourceTrinity-Large-Thinking—Not directly comparable
SWE-bench Pro
Qwen3.7 Max60.6%SourceTrinity-Large-Thinking—Not directly comparable
SWE Multilingual
Qwen3.7 Max78.3%SourceTrinity-Large-Thinking—Not directly comparable
NL2Repo
Qwen3.7 Max47.2%SourceTrinity-Large-Thinking—Not directly comparable
SciCode
Qwen3.7 Max53.5%SourceTrinity-Large-Thinking—Not directly comparable
LiveCodeBench
Qwen3.7 Max91.6%SourceTrinity-Large-Thinking—Not directly comparable
Terminal-Bench 2.0
Qwen3.7 Max69.7%SourceTrinity-Large-Thinking—Not directly comparable
SWE-bench Verified*
Qwen3.7 Max—Trinity-Large-Thinking63.2%SourceNot directly comparable
Reasoning
Knowledge
GPQA
Qwen3.7 Max92.4%SourceTrinity-Large-Thinking—Not directly comparable
GPQA-D
Qwen3.7 Max92.4%SourceTrinity-Large-Thinking76.3%SourceQwen3.7 Max leads this result
HLE
Qwen3.7 Max41.4%SourceTrinity-Large-Thinking—Not directly comparable
MMLU-Pro
Qwen3.7 Max89.6%SourceTrinity-Large-Thinking—Not directly comparable
MMLU-Redux
Qwen3.7 Max95%SourceTrinity-Large-Thinking—Not directly comparable
SuperGPQA
Qwen3.7 Max73.6%SourceTrinity-Large-Thinking—Not directly comparable
MMMLU
Qwen3.7 Max90.3%SourceTrinity-Large-Thinking—Not directly comparable
MMLU-Pro (Arcee)
Qwen3.7 Max—Trinity-Large-Thinking83.4%SourceNot directly comparable
Math
HMMT Feb 2026
Qwen3.7 Max97.1%SourceTrinity-Large-Thinking—Not directly comparable
IMOAnswerBench
Qwen3.7 Max90.0%SourceTrinity-Large-Thinking—Not directly comparable
Apex
Qwen3.7 Max44.5%SourceTrinity-Large-Thinking—Not directly comparable
AIME25 (Arcee)
Qwen3.7 Max—Trinity-Large-Thinking96.3%SourceNot directly comparable
Multilingual
MMLU-ProX
Qwen3.7 Max87%SourceTrinity-Large-Thinking—Not directly comparable
NOVA-63
Qwen3.7 Max59.0%SourceTrinity-Large-Thinking—Not directly comparable
INCLUDE
Qwen3.7 Max86.2%SourceTrinity-Large-Thinking—Not directly comparable
MAXIFE
Qwen3.7 Max89.2%SourceTrinity-Large-Thinking—Not directly comparable
PolyMath
Qwen3.7 Max86.5%SourceTrinity-Large-Thinking—Not directly comparable
Instruction following
Frequently asked questions
Which is better, Qwen3.7 Max or Trinity-Large-Thinking?
Qwen3.7 Max has the higher public score estimate, 71.6 versus 47.88, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Qwen3.7 Max or Trinity-Large-Thinking?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Qwen3.7 Max or Trinity-Large-Thinking?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Qwen3.7 Max or Trinity-Large-Thinking?
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, Qwen3.7 Max or Trinity-Large-Thinking?
Qwen3.7 Max has the larger documented context window: 1M, compared with 512K.
Related comparisons
Last updated August 18, 2026
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