Updated November 13, 2026. Rank says Qwen3.6 Plus is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Qwen3.6 Plus has the higher public point estimate, 53.43 versus 43.24. Their conditional score ranges overlap. These ranges do not establish rank confidence. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Arcee AI
43.24/100
Estimated · Public rank #133
Conditional range 28.9–57.6
Qwen3.6 Plus: No comparable API price
Trinity-Large-Thinking: $0.25 input / $0.90 output
Qwen3.6 Plus: 1M
Trinity-Large-Thinking: 512K
Qwen3.6 Plus: April 2, 2026
Trinity-Large-Thinking: March 10, 2026
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.
Code generation, repair, and software-engineering tasks
Qwen3.6 Plus
Qwen3.6 Plus has the higher public coding point estimate, 39.9 to 18.6, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Prompts that approach the documented context limit
Qwen3.6 Plus
Qwen3.6 Plus has the larger documented context window.
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Trinity-Large-Thinking is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
Like-for-like · BenchAlign v5.8
Qwen3.6 Plus has the higher coding point estimate. Conditional score ranges do not establish rank confidence.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.
We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
IFBenchInstruction following
Normalized gap 23.5Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, reasoning, multimodal, 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.
| Category | Qwen3.6 Plus | Trinity-Large-Thinking | Basis | Reading |
|---|---|---|---|---|
| Coding | 39.9Supported · #72/162 | 18.6Supported · #138/162 | Like-for-likeBenchAlign v5.8 lane · 9 vs 1 public rows | Qwen3.6 Plus leads |
| Instruction following | 85.8#50/157 | 28.9#140/157 | Like-for-likeProvisional lane · 1 vs 1 weighted rows | Qwen3.6 Plus leads |
| Agentic | 34.3Supported · #87/135 | 22.7Estimated · #117/135 | Directional onlyBenchAlign v5.8 lane · 13 vs 2 public rows | Directional only |
| Reasoning | 35.6Supported · #98/160 | 30.2Estimated · #121/160 | Directional onlyBenchAlign v5.8 lane · 2 vs 0 public rows | Directional only |
| Knowledge | 53.1Supported · #66/180 | 36.9Estimated · #129/180 | Directional onlyBenchAlign v5.8 lane · 8 vs 2 public rows | Directional only |
| Multimodal | 55.2Estimated · #46/67 | Not ranked | Not comparableBenchAlign v5.8 lane · 7 vs 0 public rows | Not comparable |
| Multilingual | 93.8#4/17 | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Math | 62.3#6/12 | Not ranked | Not comparableProvisional lane · 3 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
1K fresh input + 500 output tokens
Qwen3.6 Plus has no comparable published API token rate.
50K fresh input + 3K output tokens
Qwen3.6 Plus has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Trinity-Large-Thinking has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.6 Plus has no comparable published API token rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Qwen3.6 Plus
1M
Trinity-Large-Thinking
512K
Qwen3.6 Plus
Not sourced
Trinity-Large-Thinking
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Qwen3.6 Plus
No comparable hosted API rate
Trinity-Large-Thinking
Not published
Qwen3.6 Plus
text, image, video
Qwen Cloud model page for qwen3.6-plusTrinity-Large-Thinking
Qwen3.6 Plus
Trinity-Large-Thinking
Qwen3.6 Plus
Not sourced
Trinity-Large-Thinking
Not sourced
Qwen3.6 Plus
Reasoning
Trinity-Large-Thinking
Reasoning
Qwen3.6 Plus
Proprietary
Trinity-Large-Thinking
Open Weight
Qwen3.6 Plus
Proprietary
Trinity-Large-Thinking
Open Weight
Qwen3.6 Plus
2026-04-02
Trinity-Large-Thinking
2026-03-10
Qwen3.6 Plus has the higher public point estimate, 53.43 versus 43.24. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Qwen3.6 Plus has the higher public coding point estimate, 39.9 to 18.6, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Qwen3.6 Plus scores higher for agentic tasks on the public lane, 34.3 to 22.7. Trinity-Large-Thinking 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.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Qwen3.6 Plus has the larger documented context window: 1M, compared with 512K.
Estimates at 50,000 req/day · 1000 tokens/req average.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 2.0
Not directly comparable
Claw-Eval
Not directly comparable
QwenClawBench
Not directly comparable
τ³-bench results
Not directly comparable
VITA-Bench
Not directly comparable
DeepPlanning
Not directly comparable
Toolathlon
Not directly comparable
MCP Atlas
Not directly comparable
MCP-Tasks
Not directly comparable
WideResearch
Not directly comparable
Gert Labs
Shared sourceQwen3.6 Plus leads this result
ResearchClawBench
Not directly comparable
Terminal-Bench 2.1 (Vals)
Not directly comparable
τ²-bench Airline
Not directly comparable
SWE-bench Verified
Not directly comparable
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
LiveCodeBench v6
Not directly comparable
NL2Repo
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
Vibe Code Bench
Not directly comparable
LiveCodeBench (Vals)
Not directly comparable
SWE-bench (Vals)
Not directly comparable
SWE-bench Verified*
Not directly comparable
MMMU
Not directly comparable
MMMU-Pro
Not directly comparable
MathVision
Not directly comparable
VideoMMMU
Not directly comparable
ScreenSpot Pro
Not directly comparable
CharXiv
Not directly comparable
V*
Not directly comparable
GPQA
Not directly comparable
SuperGPQA
Not directly comparable
MMLU-Pro
Not directly comparable
MMLU-Redux
Not directly comparable
C-Eval
Not directly comparable
HLE
Not directly comparable
GPQA Diamond (Vals)
Not directly comparable
MMLU-Pro (Vals)
Not directly comparable
GPQA-D
Not directly comparable
MMLU-Pro (Arcee)
Not directly comparable
AIME26
Not directly comparable
HMMT Feb 2025
Not directly comparable
HMMT Nov 2025
Not directly comparable
HMMT Feb 2026
Not directly comparable
MMAnswerBench
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Not directly comparable
AIME25 (Arcee)
Not directly comparable
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Last updated November 13, 2026
