Updated October 14, 2026. Rank says MiniMax M2.7 is ahead. Price, access, and your workload can each overturn that. 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
MiniMax M2.7 has the higher public point estimate, 48.18 versus 47.25. Their conditional score ranges overlap. These ranges do not establish rank confidence. 9 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 M2.7
MiniMax M2.7 has the higher public coding point estimate, 34.5 to 21.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Tool use, computer use, and multi-step task completion
MiniMax M2.7
MiniMax M2.7 has the higher public agentic point estimate, 32.6 to 28.2, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Prompts that approach the documented context limit
Nemotron 3 Ultra
Nemotron 3 Ultra has the larger documented context window.
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. MiniMax M2.7 does not fit this workload in one request. MiniMax M2.7 has no published cached-input rate, so cached tokens use its listed input rate. Nemotron 3 Ultra has no comparable published API token rate.
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 M2.7 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 MultilingualCoding
Normalized gap 8.8LiveCodeBench (Vals)Coding
Normalized gap 6.1MMLU-Pro (Vals)Knowledge
Normalized gap 5.4HLEKnowledge
Normalized gap 1.3Each 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 | MiniMax M2.7 | Nemotron 3 Ultra | Basis | Reading |
|---|---|---|---|---|
| Agentic | 32.6Supported · #88/125 | 28.2Supported · #95/125 | Like-for-likeBenchAlign v5.8 lane · 8 vs 6 public rows | MiniMax M2.7 leads · intervals overlap |
| Coding | 34.5Supported · #79/149 | 21.9Supported · #115/149 | Like-for-likeBenchAlign v5.8 lane · 12 vs 7 public rows | MiniMax M2.7 leads · intervals overlap |
| Knowledge | 46.0Supported · #91/181 | 50.4Estimated · #77/181 | Directional onlyBenchAlign v5.8 lane · 5 vs 7 public rows | Directional only |
| Instruction following | 93.0#13/144 | 92.1#20/144 | Directional onlyProvisional lane · 0 vs 1 weighted rows | Directional only |
| Reasoning | 79.6Unranked · 2 rankable rows | 70.8#20/29 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | 89.2#7/17 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | 70.5Unranked · 4 rankable rows | Not ranked | Not comparableProvisional lane · 2 vs 0 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
Nemotron 3 Ultra has no comparable published API token rate.
50K fresh input + 3K output tokens
Nemotron 3 Ultra has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
MiniMax M2.7 does not fit this workload in one request. MiniMax M2.7 has no published cached-input rate, so cached tokens use its listed input rate. Nemotron 3 Ultra 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 M2.7
200K
Nemotron 3 Ultra
1M
MiniMax M2.7
Not sourced
Nemotron 3 Ultra
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
MiniMax M2.7
Not published
Nemotron 3 Ultra
No comparable hosted API rate
MiniMax M2.7
Not sourced
Nemotron 3 Ultra
Not sourced
MiniMax M2.7
Not sourced
Nemotron 3 Ultra
Not sourced
MiniMax M2.7
Not sourced
Nemotron 3 Ultra
Not sourced
MiniMax M2.7
Non-Reasoning
Nemotron 3 Ultra
Reasoning
MiniMax M2.7
Open Weight
Nemotron 3 Ultra
Open Weight
MiniMax M2.7
Open Weight
Nemotron 3 Ultra
Open Weight
MiniMax M2.7
2026-03-18
Nemotron 3 Ultra
2026-06-04
MiniMax M2.7 has the higher public point estimate, 48.18 versus 47.25. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
MiniMax M2.7 has the higher public coding point estimate, 34.5 to 21.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
MiniMax M2.7 has the higher public agentic tasks point estimate, 32.6 to 28.2, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Nemotron 3 Ultra has the larger documented context window: 1M, compared with 200K.
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
τ³-bench results
Nemotron 3 Ultra leads this result
Toolathlon
Not directly comparable
MLE-Bench Lite
Not directly comparable
MM-ClawBench
Not directly comparable
Claw-Eval
Not directly comparable
Gert Labs
Not directly comparable
Terminal-Bench 2.1 (Vals)
Nemotron 3 Ultra leads this result
Terminal-Bench 2.1
Not directly comparable
PinchBench
Not directly comparable
BrowseComp
Not directly comparable
HLE w/ tools
Not directly comparable
SWE-bench Verified*
Not directly comparable
SWE-bench Pro
Not directly comparable
SWE-Rebench
Not directly comparable
SWE Multilingual
MiniMax M2.7 leads this result
Multi-SWE Bench
Not directly comparable
VIBE-Pro
Not directly comparable
NL2Repo
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
Vibe Code Bench
Not directly comparable
React Native Evals
Not directly comparable
LiveCodeBench (Vals)
Nemotron 3 Ultra leads this result
SWE-bench (Vals)
MiniMax M2.7 leads this result
SWE-bench Verified
Not directly comparable
LiveCodeBench v6
Not directly comparable
SciCode
Not directly comparable
Terminal-Bench 2.1
Not directly comparable
HLE
MiniMax M2.7 leads this result
GPQA-D
Tie
MMLU-Pro (Arcee)
Not directly comparable
GPQA Diamond (Vals)
MiniMax M2.7 leads this result
MMLU-Pro (Vals)
Nemotron 3 Ultra leads this result
GPQA
Not directly comparable
HLE w/o tools
Not directly comparable
MMLU-Pro
Not directly comparable
MMLU-ProX
Not directly comparable
IFBench
Not directly comparable
AIME25 (Arcee)
Not directly comparable
AIME26
Not directly comparable
HMMT Nov 2025
Not directly comparable
HMMT Feb 2026
Not directly comparable
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Last updated October 14, 2026
