Agentic
Not comparable- MiMo-V2.5
- 51.1
- Estimated · #58/151
- Nemotron 3 Super 100B
- Not ranked
- Basis
- BenchAlign lane · 6 vs 1 public rows
- Reading
- Not comparable
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
See the free Radar BriefUpdated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
MiMo-V2.5 has the higher public score estimate, 60.72 versus 49.65, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Nemotron 3 Super 100B is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Nemotron 3 Super 100B is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
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.
Each row shows the public-lane category score for both models: the BenchAlign 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 | Nemotron 3 Super 100B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 51.1Estimated · #58/151 | Not ranked | Not comparableBenchAlign lane · 6 vs 1 public rows | Not comparable |
| Coding | 54.8Estimated · #45/183 | Not ranked | Not comparableBenchAlign lane · 4 vs 0 public rows | Not comparable |
| Reasoning | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | 53.8Estimated · #65/181 | Not ranked | Not comparableBenchAlign lane · 2 vs 0 public rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 58.5#29/48 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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. Nemotron 3 Super 100B has no comparable published API token rate.
50K fresh input + 3K output tokens
MiMo-V2.5 has no comparable published API token rate. Nemotron 3 Super 100B 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. Nemotron 3 Super 100B 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
Nemotron 3 Super 100B
1M
MiMo-V2.5
Not sourced
Nemotron 3 Super 100B
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
Nemotron 3 Super 100B
No comparable hosted API rate
MiMo-V2.5
Not sourced
Nemotron 3 Super 100B
Not sourced
MiMo-V2.5
Not sourced
Nemotron 3 Super 100B
Not sourced
MiMo-V2.5
Not sourced
Nemotron 3 Super 100B
Not sourced
MiMo-V2.5
Reasoning
Nemotron 3 Super 100B
Non-Reasoning
MiMo-V2.5
Proprietary
Nemotron 3 Super 100B
Open Weight
MiMo-V2.5
Proprietary
Nemotron 3 Super 100B
Open Weight
MiMo-V2.5
2026-04-22
Nemotron 3 Super 100B
2026-01-15
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Claw-Eval
Shared sourceMiMo-V2.5 leads this result
MM-ClawBench
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
Gert Labs
Not directly comparable
ResearchClawBench
Not directly comparable
Terminal-Bench 2.1 (Vals)
Not directly comparable
SWE-bench Pro
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
LiveCodeBench (Vals)
Not directly comparable
SWE-bench (Vals)
Not directly comparable
MiMo-V2.5 has the higher public score estimate, 60.72 versus 49.65, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Nemotron 3 Super 100B is not ranked on the public lane for coding, so no winner is named for coding.
Nemotron 3 Super 100B is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
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.
Last updated September 4, 2026
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