1-bit Bonsai 4B vs Qwen3.6 Plus

Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.

Agentic
Coding
Multimodal & Grounded
Reasoning
Knowledge
Instruction Following
Multilingual
Mathematics

1-bit Bonsai 4B· Qwen3.6 Plus

Quick Verdict

Pick Qwen3.6 Plus if you want the stronger benchmark profile. 1-bit Bonsai 4B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.

Qwen3.6 Plus is clearly ahead on the aggregate, 69 to 44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.6 Plus's sharpest advantage is in knowledge, where it averages 66 against 28.7. The single biggest benchmark swing on the page is GPQA, 28.7% to 90.4%.

Qwen3.6 Plus is the reasoning model in the pair, while 1-bit Bonsai 4B 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. Qwen3.6 Plus gives you the larger context window at 1M, compared with 32K for 1-bit Bonsai 4B.

Operational tradeoffs

PriceFree*Free*
SpeedN/AN/A
TTFTN/AN/A
Context32K1M

Decision framing

BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.

Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.

Benchmark1-bit Bonsai 4BQwen3.6 Plus
Agentic
Terminal-Bench 2.061.6%
Claw-Eval58.7%
QwenClawBench57.2%
QwenWebBench1502
TAU3-Bench70.7%
VITA-Bench44.3%
DeepPlanning41.5%
Toolathlon39.8%
MCP Atlas48.2%
MCP-Tasks74.1%
WideResearch74.3%
OSWorld-Verified62.5%
Coding
SWE-bench Verified78.8%
SWE-bench Pro56.6%
SWE Multilingual73.8%
LiveCodeBench v687.1%
NL2Repo37.9%
Multimodal & Grounded
MMMU86.0%
MMMU-Pro78.8%
RealWorldQA85.4%
OmniDocBench 1.591.2%
Video-MME (with subtitle)87.8%
Video-MME (w/o subtitle)84.2%
MathVision88.0%
We-Math89.0%
DynaMath88.0%
MStar83.3%
SimpleVQA67.3%
ChatCVQA81.5%
MMLongBench-Doc62.0%
CC-OCR83.4%
AI2D_TEST94.4%
CountBench97.6%
RefCOCO (avg)93.5%
ODINW1351.8%
ERQA65.7%
VideoMMMU84.0%
MLVU (M-Avg)86.7%
ScreenSpot Pro68.2%
ReasoningQwen3.6 Plus wins
MuSR41.4%
AI-Needle68.3%
LongBench v262%
KnowledgeQwen3.6 Plus wins
GPQA28.7%90.4%
SuperGPQA71.6%
MMLU-Pro88.5%
MMLU-Redux94.5%
C-Eval93.3%
HLE28.8%
Instruction FollowingQwen3.6 Plus wins
IFEval69.6%94.3%
IFBench74.2%
Multilingual
MMLU-ProX84.7%
NOVA-6357.9%
INCLUDE85.1%
PolyMath77.4%
VWT2k-lite84.3%
MAXIFE88.2%
Mathematics
MATH-50065.8%
AIME2695.3%
HMMT Feb 202596.7%
HMMT Nov 202594.6%
HMMT Feb 202687.8%
MMAnswerBench83.8%
Frequently Asked Questions (4)

Which is better, 1-bit Bonsai 4B or Qwen3.6 Plus?

Qwen3.6 Plus is ahead overall, 69 to 44. The biggest single separator in this matchup is GPQA, where the scores are 28.7% and 90.4%.

Which is better for knowledge tasks, 1-bit Bonsai 4B or Qwen3.6 Plus?

Qwen3.6 Plus has the edge for knowledge tasks in this comparison, averaging 66 versus 28.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for reasoning, 1-bit Bonsai 4B or Qwen3.6 Plus?

Qwen3.6 Plus has the edge for reasoning in this comparison, averaging 62 versus 41.4. 1-bit Bonsai 4B stays close enough that the answer can still flip depending on your workload.

Which is better for instruction following, 1-bit Bonsai 4B or Qwen3.6 Plus?

Qwen3.6 Plus has the edge for instruction following in this comparison, averaging 94.3 versus 69.6. Inside this category, IFEval is the benchmark that creates the most daylight between them.

Last updated: April 2, 2026

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