Long documents
Prompts that approach the documented context limit
Qwen3.6 Plus
Qwen3.6 Plus has the larger documented context window.
Confidence: documented
Qwen3.6 Plus vs Ternary Bonsai 2 27B
Updated October 29, 2026. Rank cannot separate these two. Price, access, and your workload decide. Public scores include evidence status and uncertainty.
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Decision reading
Ternary Bonsai 2 27B has the higher public point estimate, 53.95 versus 53.54. Their conditional score ranges overlap. These ranges do not establish rank confidence. 7 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 7
- Qwen3.6 Plus only
- 42
- Ternary Bonsai 2 27B only
- 14
- Like-for-like categories
- 1 / 8
Supported: Qwen3.6 Plus · Estimated: Ternary Bonsai 2 27B. Conditional ranges do not establish rank confidence.How the comparison works
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.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Ternary Bonsai 2 27B is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Ternary Bonsai 2 27B is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedChat 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-ratesCache-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-ratesRepository 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
Which one for a specific job
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.
40.1Qwen3.6 Plus—Ternary Bonsai 2 27B
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
42 Qwen3.6 Plus only
7 Shared
14 Ternary Bonsai 2 27B only
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.
SWE-bench VerifiedCoding
Normalized gap 18.0Qwen3.6 Plus:78.8%Ternary Bonsai 2 27B:60.8%GPQAKnowledge
Normalized gap 4.6Qwen3.6 Plus:90.4%Ternary Bonsai 2 27B:85.8%IFBenchInstruction following
Normalized gap 1.8Qwen3.6 Plus:75.8%Ternary Bonsai 2 27B:74%AIME26Math
Normalized gap 0.5Qwen3.6 Plus:95.3%Ternary Bonsai 2 27B:95.8%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 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.
Instruction following
Like-for-like- Qwen3.6 Plus
- 85.8
- #50/157
- Ternary Bonsai 2 27B
- 74.0
- #73/157
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Qwen3.6 Plus leads
Agentic
Not comparable- Qwen3.6 Plus
- 35.1
- Supported · #91/135
- Ternary Bonsai 2 27B
- Not ranked
- Basis
- BenchAlign v5.8 lane · 13 vs 3 public rows
- Reading
- Not comparable
Coding
Not comparable- Qwen3.6 Plus
- 40.1
- Supported · #68/156
- Ternary Bonsai 2 27B
- Not ranked
- Basis
- BenchAlign v5.8 lane · 9 vs 4 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Qwen3.6 Plus
- 73.9
- Unranked · 4 rankable rows
- Ternary Bonsai 2 27B
- 77.9
- Unranked · 1 rankable row
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Qwen3.6 Plus
- 75.8
- #24/58
- Ternary Bonsai 2 27B
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Qwen3.6 Plus
- 52.1
- Supported · #68/179
- Ternary Bonsai 2 27B
- Not ranked
- Basis
- BenchAlign v5.8 lane · 8 vs 3 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Qwen3.6 Plus
- 93.8
- #4/17
- Ternary Bonsai 2 27B
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Qwen3.6 Plus
- 69.5
- #6/12
- Ternary Bonsai 2 27B
- 86.2
- Unranked · 4 rankable rows
- Basis
- Provisional lane · 3 vs 1 weighted rows
- Reading
- Not comparable
| Category | Qwen3.6 Plus | Ternary Bonsai 2 27B | Basis | Reading |
|---|---|---|---|---|
| Instruction following | 85.8#50/157 | 74.0#73/157 | Like-for-likeProvisional lane · 1 vs 1 weighted rows | Qwen3.6 Plus leads |
| Agentic | 35.1Supported · #91/135 | Not ranked | Not comparableBenchAlign v5.8 lane · 13 vs 3 public rows | Not comparable |
| Coding | 40.1Supported · #68/156 | Not ranked | Not comparableBenchAlign v5.8 lane · 9 vs 4 public rows | Not comparable |
| Reasoning | 73.9Unranked · 4 rankable rows | 77.9Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Multimodal | 75.8#24/58 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Knowledge | 52.1Supported · #68/179 | Not ranked | Not comparableBenchAlign v5.8 lane · 8 vs 3 public rows | Not comparable |
| Multilingual | 93.8#4/17 | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Math | 69.5#6/12 | 86.2Unranked · 4 rankable rows | Not comparableProvisional lane · 3 vs 1 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, 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.
Supported evidence per lane · bars run 0–100Methodology
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
- Qwen3.6 Plus
- API rate not published
- Fits in one request
- Ternary Bonsai 2 27B
- Self-hosted; infrastructure cost varies
- Fits in one request
Qwen3.6 Plus has no comparable published API token rate. Ternary Bonsai 2 27B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Qwen3.6 Plus
- API rate not published
- Fits in one request
- Ternary Bonsai 2 27B
- Self-hosted; infrastructure cost varies
- Fits in one request
Qwen3.6 Plus has no comparable published API token rate. Ternary Bonsai 2 27B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Qwen3.6 Plus
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Ternary Bonsai 2 27B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Qwen3.6 Plus has no comparable published API token rate. Ternary Bonsai 2 27B has no comparable published API token rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationQwen3.6 PlusTernary Bonsai 2 27B
Context window
Maximum documented context; output-token limits may be lower.
Qwen3.6 Plus
1M
Ternary Bonsai 2 27B
API model ID
Qwen3.6 Plus
Not sourced
Ternary Bonsai 2 27B
prism-ml/Ternary-Bonsai-2-27B-gguf
PrismML Bonsai 2 collectionCached-input rate
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
Ternary Bonsai 2 27B
No comparable hosted API rate
PrismML Bonsai 2 collectionDocumented inputs
Qwen3.6 Plus
Not sourced
Ternary Bonsai 2 27B
Not sourced
Documented outputs
Qwen3.6 Plus
Not sourced
Ternary Bonsai 2 27B
Not sourced
Provider availability
Qwen3.6 Plus
Not sourced
Ternary Bonsai 2 27B
Not sourced
Reasoning profile
Qwen3.6 Plus
Reasoning
Ternary Bonsai 2 27B
Reasoning
Weight access
Qwen3.6 Plus
Proprietary
Ternary Bonsai 2 27B
Open Weight
License
Qwen3.6 Plus
Proprietary
Ternary Bonsai 2 27B
Open Weight
Release date
Qwen3.6 Plus
2026-04-02
Ternary Bonsai 2 27B
2026-09-17
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
- Ternary Bonsai 2 27B has the higher public point estimate, 53.95 versus 53.54. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- 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.
Questions
Which is better, Qwen3.6 Plus or Ternary Bonsai 2 27B?
Ternary Bonsai 2 27B has the higher public point estimate, 53.95 versus 53.54. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Qwen3.6 Plus or Ternary Bonsai 2 27B?
Ternary Bonsai 2 27B is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Qwen3.6 Plus or Ternary Bonsai 2 27B?
Ternary Bonsai 2 27B is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Qwen3.6 Plus or Ternary Bonsai 2 27B?
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, Qwen3.6 Plus or Ternary Bonsai 2 27B?
Qwen3.6 Plus has the larger documented context window: 1M, compared with 262K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence63 rows
Agentic
Terminal-Bench 2.0
Qwen3.6 Plus61.6%SourceTernary Bonsai 2 27B—Not directly comparable
Claw-Eval
Qwen3.6 Plus58.8%SourceTernary Bonsai 2 27B—Not directly comparable
QwenClawBench
Qwen3.6 Plus57.2%SourceTernary Bonsai 2 27B—Not directly comparable
τ³-bench results
Qwen3.6 Plus70.7%SourceTernary Bonsai 2 27B—Not directly comparable
VITA-Bench
Qwen3.6 Plus44.3%SourceTernary Bonsai 2 27B—Not directly comparable
DeepPlanning
Qwen3.6 Plus41.5%SourceTernary Bonsai 2 27B—Not directly comparable
Toolathlon
Qwen3.6 Plus39.8%SourceTernary Bonsai 2 27B—Not directly comparable
MCP Atlas
Qwen3.6 Plus48.2%SourceTernary Bonsai 2 27B—Not directly comparable
MCP-Tasks
Qwen3.6 Plus74.1%SourceTernary Bonsai 2 27B—Not directly comparable
WideResearch
Qwen3.6 Plus74.3%SourceTernary Bonsai 2 27B—Not directly comparable
Gert Labs
Qwen3.6 Plus50.60%SourceTernary Bonsai 2 27B—Not directly comparable
ResearchClawBench
Qwen3.6 Plus18.0%SourceTernary Bonsai 2 27B—Not directly comparable
Terminal-Bench 2.1 (Vals)
Qwen3.6 Plus53.2%SourceTernary Bonsai 2 27B—Not directly comparable
τ²-bench results
Qwen3.6 Plus—Ternary Bonsai 2 27B80.2%SourceNot directly comparable
BFCL v3
Qwen3.6 Plus—Ternary Bonsai 2 27B74.9%SourceNot directly comparable
Terminal-Bench 2.1
Qwen3.6 Plus—Ternary Bonsai 2 27B52.8%SourceNot directly comparable
Coding
SWE-bench Verified
Qwen3.6 Plus78.8%SourceTernary Bonsai 2 27B60.8%SourceQwen3.6 Plus leads this result
SWE-bench Pro
Qwen3.6 Plus56.6%SourceTernary Bonsai 2 27B—Not directly comparable
SWE Multilingual
Qwen3.6 Plus73.8%SourceTernary Bonsai 2 27B—Not directly comparable
LiveCodeBench v6
Qwen3.6 Plus87.1%SourceTernary Bonsai 2 27B90.1%SourceTernary Bonsai 2 27B leads this result
NL2Repo
Qwen3.6 Plus37.9%SourceTernary Bonsai 2 27B—Not directly comparable
Terminal-Bench 2.0
Qwen3.6 Plus61.6%SourceTernary Bonsai 2 27B—Not directly comparable
Vibe Code Bench
Qwen3.6 Plus25.56%SourceTernary Bonsai 2 27B—Not directly comparable
LiveCodeBench (Vals)
Qwen3.6 Plus86.0%SourceTernary Bonsai 2 27B—Not directly comparable
SWE-bench (Vals)
Qwen3.6 Plus73.4%SourceTernary Bonsai 2 27B—Not directly comparable
BigCodeBench
Qwen3.6 Plus—Ternary Bonsai 2 27B58.1%SourceNot directly comparable
Terminal-Bench 2.1
Qwen3.6 Plus—Ternary Bonsai 2 27B52.8%SourceNot directly comparable
Reasoning
Multimodal
MMMU
Qwen3.6 Plus86.0%SourceTernary Bonsai 2 27B—Not directly comparable
MMMU-Pro
Qwen3.6 Plus78.8%SourceTernary Bonsai 2 27B—Not directly comparable
MathVision
Qwen3.6 Plus88.0%SourceTernary Bonsai 2 27B—Not directly comparable
VideoMMMU
Qwen3.6 Plus84.0%SourceTernary Bonsai 2 27B—Not directly comparable
ScreenSpot Pro
Qwen3.6 Plus68.2%SourceTernary Bonsai 2 27B—Not directly comparable
CharXiv
Qwen3.6 Plus81.5%SourceTernary Bonsai 2 27B—Not directly comparable
V*
Qwen3.6 Plus96.9%SourceTernary Bonsai 2 27B—Not directly comparable
CharXiv (overall)
Qwen3.6 Plus—Ternary Bonsai 2 27B80.0%SourceNot directly comparable
A-OKVQA
Qwen3.6 Plus—Ternary Bonsai 2 27B86.8%SourceNot directly comparable
OmniDocBench 1.6
Qwen3.6 Plus—Ternary Bonsai 2 27B89.1%SourceNot directly comparable
RealWorldQA
Qwen3.6 Plus—Ternary Bonsai 2 27B80.1%SourceNot directly comparable
OCRBench V2
Qwen3.6 Plus—Ternary Bonsai 2 27B56.9%SourceNot directly comparable
Knowledge
GPQA
Qwen3.6 Plus90.4%SourceTernary Bonsai 2 27B85.8%SourceQwen3.6 Plus leads this result
SuperGPQA
Qwen3.6 Plus71.6%SourceTernary Bonsai 2 27B—Not directly comparable
MMLU-Pro
Qwen3.6 Plus88.5%SourceTernary Bonsai 2 27B—Not directly comparable
MMLU-Redux
Qwen3.6 Plus94.5%SourceTernary Bonsai 2 27B89.1%SourceQwen3.6 Plus leads this result
C-Eval
Qwen3.6 Plus93.3%SourceTernary Bonsai 2 27B—Not directly comparable
HLE
Qwen3.6 Plus28.8%SourceTernary Bonsai 2 27B—Not directly comparable
GPQA Diamond (Vals)
Qwen3.6 Plus87.4%SourceTernary Bonsai 2 27B—Not directly comparable
MMLU-Pro (Vals)
Qwen3.6 Plus87.7%SourceTernary Bonsai 2 27B—Not directly comparable
GPQA-D
Qwen3.6 Plus—Ternary Bonsai 2 27B85.8%SourceNot directly comparable
Multilingual
Instruction following
Math
AIME26
Qwen3.6 Plus95.3%SourceTernary Bonsai 2 27B95.8%SourceTernary Bonsai 2 27B leads this result
HMMT Feb 2025
Qwen3.6 Plus96.7%SourceTernary Bonsai 2 27B—Not directly comparable
HMMT Nov 2025
Qwen3.6 Plus94.6%SourceTernary Bonsai 2 27B—Not directly comparable
HMMT Feb 2026
Qwen3.6 Plus87.8%SourceTernary Bonsai 2 27B—Not directly comparable
MMAnswerBench
Qwen3.6 Plus83.8%SourceTernary Bonsai 2 27B—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Qwen3.6 Plus38.246%SourceTernary Bonsai 2 27B—Not directly comparable
GSM8K
Qwen3.6 Plus—Ternary Bonsai 2 27B96.7%SourceNot directly comparable
MATH-500
Qwen3.6 Plus—Ternary Bonsai 2 27B98.8%SourceNot directly comparable
AIME 2025
Qwen3.6 Plus—Ternary Bonsai 2 27B95%SourceNot directly comparable
63 public results · 7 shared
Watch Qwen3.6 Plus vs Ternary Bonsai 2 27B
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Last updated October 29, 2026