Updated October 14, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 10 results are shared. Category rows resting on Estimated evidence or 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.
Code generation, repair, and software-engineering tasks
MiniMax M3
MiniMax M3 has the higher public coding point estimate, 36.5 to 34.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Tool use, computer use, and multi-step task completion
Not enough matched evidence
MiMo-V2.5 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
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
MiniMax M3 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.
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 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.
SWE-bench ProCoding
Normalized gap 2.9MMLU-Pro (Vals)Knowledge
Normalized gap 1.3LiveCodeBench (Vals)Coding
Normalized gap 0.7MMMU-ProMultimodal
Normalized gap 0.2Each 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.
| Category | MiMo-V2.5 | MiniMax M3 | Basis | Reading |
|---|---|---|---|---|
| Coding | 34.7Supported · #78/149 | 36.5Supported · #73/149 | Like-for-likeBenchAlign v5.8 lane · 4 vs 10 public rows | MiniMax M3 leads · intervals overlap |
| Agentic | 32.8Estimated · #84/125 | 39.6Supported · #66/125 | Directional onlyBenchAlign v5.8 lane · 6 vs 9 public rows | Directional only |
| Multimodal | 72.2#31/54 | 61.5#43/54 | Directional onlyProvisional lane · 2 vs 2 weighted rows | Directional only |
| Reasoning | Not ranked | 82.9#5/29 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | 49.6Supported · #80/181 | Not comparableBenchAlign v5.8 lane · 2 vs 2 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 93.8#5/144 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 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.
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
MiMo-V2.5 has no comparable published API token rate.
50K fresh input + 3K output tokens
MiMo-V2.5 has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
MiMo-V2.5 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.
MiMo-V2.5
1M
MiniMax M3
1M
MiMo-V2.5
Not sourced
MiniMax M3
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
MiMo-V2.5
No comparable hosted API rate
MiniMax M3
$0.06 per 1M cached input tokens
MiMo-V2.5
Not sourced
MiniMax M3
Not sourced
MiMo-V2.5
Not sourced
MiniMax M3
Not sourced
MiMo-V2.5
Not sourced
MiniMax M3
Not sourced
MiMo-V2.5
Reasoning
MiniMax M3
Non-Reasoning
MiMo-V2.5
Proprietary
MiniMax M3
Open Weight
MiMo-V2.5
Proprietary
MiniMax M3
Open Weight
MiMo-V2.5
2026-04-22
MiniMax M3
2026-06-01
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
MiniMax M3 has the higher public coding point estimate, 36.5 to 34.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
MiniMax M3 scores higher for agentic tasks on the public lane, 39.6 to 32.8. MiMo-V2.5 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.
Both models list the same context window, 1M.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Claw-Eval
MiniMax M3 leads this result
MM-ClawBench
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
Gert Labs
Not directly comparable
ResearchClawBench
Shared sourceMiniMax M3 leads this result
Terminal-Bench 2.1 (Vals)
MiMo-V2.5 leads this result
Terminal-Bench 2.1
Not directly comparable
BrowseComp
Not directly comparable
OSWorld-Verified
Not directly comparable
MCP Atlas
Not directly comparable
BankerToolBench
Not directly comparable
OSWorld 2.0
Not directly comparable
SWE-bench Pro
MiniMax M3 leads this result
Terminal-Bench 2.0
Not directly comparable
LiveCodeBench (Vals)
MiniMax M3 leads this result
SWE-bench (Vals)
MiniMax M3 leads this result
SWE-bench Verified
Not directly comparable
Terminal-Bench 2.1
Not directly comparable
NL2Repo
Not directly comparable
VIBE V2
Not directly comparable
SVG-Bench
Not directly comparable
KernelBench Hard
Not directly comparable
OpenHarmony Bench
Not directly comparable
Video-MME (with subtitle)
MiMo-V2.5 leads this result
CharXiv
Not directly comparable
MMMU-Pro
MiniMax M3 leads this result
OfficeQA Pro
Not directly comparable
OmniDocBench 1.5
Not directly comparable
VideoMMMU
Not directly comparable
USAMO 2026
Not directly comparable
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Last updated October 14, 2026
