Agentic
Directional only- MiniMax M3
- 72.3
- Qwen3.6-27B
- 59.3
- Weighted basis
- 3 vs 1 rows
- Reading
- Directional only
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
Start the free Radar BriefUpdated August 30, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
MiniMax M3 has the higher public score estimate, 68.73 versus 53.84, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
9 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Prompts that approach the documented context limit
MiniMax M3
MiniMax M3 has the larger documented context window.
Confidence: documented
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
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
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
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
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
| Category | MiniMax M3 | Qwen3.6-27B | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 72.3 | 59.3 | Directional only3 vs 1 rows | Directional only |
| Coding | 72.2 | 77.5 | Directional only2 vs 3 rows | Directional only |
| Multimodal | 64.9 | 76.7 | Directional only2 vs 2 rows | Directional only |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | Not measured | 53.3 | Not comparable0 vs 4 rows | Not comparable |
| Math | 85.7 | 89.2 | Not comparable1 vs 2 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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.
Terminal-Bench 2.0
Agentic
SWE-bench Pro
Coding
SWE-bench Verified
Coding
MMMU-Pro
Multimodal
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
Qwen3.6-27B has no comparable published API token rate.
50K fresh input + 3K output tokens
Qwen3.6-27B has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Qwen3.6-27B 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.
MiniMax M3
1M
Qwen3.6-27B
262K
MiniMax M3
Not sourced
Qwen3.6-27B
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
MiniMax M3
$0.06 per 1M cached input tokens
Qwen3.6-27B
No comparable hosted API rate
MiniMax M3
Not sourced
Qwen3.6-27B
Not sourced
MiniMax M3
Not sourced
Qwen3.6-27B
Not sourced
MiniMax M3
Not sourced
Qwen3.6-27B
Not sourced
MiniMax M3
Non-Reasoning
Qwen3.6-27B
Reasoning
MiniMax M3
Open Weight
Qwen3.6-27B
Open Weight
MiniMax M3
Open Weight
Qwen3.6-27B
Open Weight
MiniMax M3
2026-06-01
Qwen3.6-27B
2026-04-21
Run the same representative tasks against both endpoints before changing production traffic.
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
MiniMax M3 leads this result
BrowseComp
Not directly comparable
OSWorld-Verified
Not directly comparable
MCP Atlas
Not directly comparable
Claw-Eval
MiniMax M3 leads this result
BankerToolBench
Not directly comparable
ResearchClawBench
Not directly comparable
OSWorld 2.0
Not directly comparable
QwenClawBench
Not directly comparable
QwenWebBench
Not directly comparable
AndroidWorld
Not directly comparable
Gert Labs
Not directly comparable
SWE-bench Verified
MiniMax M3 leads this result
SWE-bench Pro
MiniMax M3 leads this result
Terminal-Bench 2.0
MiniMax M3 leads this result
NL2Repo
MiniMax M3 leads this result
VIBE V2
Not directly comparable
SVG-Bench
Not directly comparable
KernelBench Hard
Not directly comparable
OpenHarmony Bench
Not directly comparable
SWE Multilingual
Not directly comparable
LiveCodeBench
Not directly comparable
MMLU-Pro
Not directly comparable
MMLU-Redux
Not directly comparable
SuperGPQA
Not directly comparable
C-Eval
Not directly comparable
GPQA
Not directly comparable
HLE
Not directly comparable
USAMO 2026
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
AIME26
Not directly comparable
OfficeQA Pro
Not directly comparable
OmniDocBench 1.5
Not directly comparable
MMMU-Pro
MiniMax M3 leads this result
VideoMMMU
MiniMax M3 leads this result
Video-MME (with subtitle)
Qwen3.6-27B leads this result
MMMU
Not directly comparable
RealWorldQA
Not directly comparable
DynaMath
Not directly comparable
MStar
Not directly comparable
SimpleVQA
Not directly comparable
CharXiv
Not directly comparable
CC-OCR
Not directly comparable
CountBench
Not directly comparable
RefCOCO (avg)
Not directly comparable
ERQA
Not directly comparable
MLVU (M-Avg)
Not directly comparable
V*
Not directly comparable
MiniMax M3 has the higher public score estimate, 68.73 versus 53.84, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. 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.
MiniMax M3 has the larger documented context window: 1M, compared with 262K.
Last updated August 30, 2026
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