Agentic
Like-for-like- Hy3 Preview
- 54.4
- MiniMax M2.7
- 57.0
- Weighted basis
- 1 vs 1 rows
- Reading
- MiniMax M2.7 leads
Provider changes are easy to miss. Radar watches releases, pricing, deprecations, and incidents at the source.Provider changes are easy to miss.
See RadarModel comparison
Updated August 7, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
MiniMax M2.7 has the higher public score, 63.1 versus 42.8, and the 90% score intervals do not overlap.
3 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.
Tool use, computer use, and multi-step task completion
MiniMax M2.7
MiniMax M2.7 leads on the same 1 weighted benchmark row.
Confidence: limited
Prompts that approach the documented context limit
Hy3 Preview
Hy3 Preview has the larger documented context window.
Confidence: documented
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
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
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. Hy3 Preview has no comparable published API token rate.
Confidence: rate-fallback
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 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 | Hy3 Preview | MiniMax M2.7 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 54.4 | 57.0 | Like-for-like1 vs 1 rows | MiniMax M2.7 leads |
| Coding | 74.4 | 53.3 | Not comparable1 vs 2 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 87.2 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 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
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
Hy3 Preview has no comparable published API token rate.
50K fresh input + 3K output tokens
Hy3 Preview 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. Hy3 Preview 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.
Hy3 Preview
256K
MiniMax M2.7
200K
Hy3 Preview
Not sourced
MiniMax M2.7
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Hy3 Preview
No comparable hosted API rate
MiniMax M2.7
Not published
Hy3 Preview
Not sourced
MiniMax M2.7
Not sourced
Hy3 Preview
Not sourced
MiniMax M2.7
Not sourced
Hy3 Preview
Not sourced
MiniMax M2.7
Not sourced
Hy3 Preview
Reasoning
MiniMax M2.7
Non-Reasoning
Hy3 Preview
Open Weight
MiniMax M2.7
Open Weight
Hy3 Preview
Open Weight
MiniMax M2.7
Open Weight
Hy3 Preview
2026-04-23
MiniMax M2.7
2026-03-18
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.
Terminal-Bench 2.0
MiniMax M2.7 leads this result
Gert Labs
Shared sourceMiniMax M2.7 leads this result
Toolathlon
Not directly comparable
MLE-Bench Lite
Not directly comparable
MM-ClawBench
Not directly comparable
Claw-Eval
Not directly comparable
SWE-bench Verified
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
SWE-bench Verified*
Not directly comparable
SWE-bench Pro
Not directly comparable
SWE-Rebench
Not directly comparable
SWE Multilingual
Not directly comparable
Multi-SWE Bench
Not directly comparable
VIBE-Pro
Not directly comparable
NL2Repo
Not directly comparable
Vibe Code Bench
Not directly comparable
React Native Evals
Not directly comparable
AIME25 (Arcee)
Not directly comparable
MiniMax M2.7 has the higher public score, 63.1 versus 42.8, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
MiniMax M2.7 leads the like-for-like agentic tasks comparison across 1 shared weighted benchmark row.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Hy3 Preview has the larger documented context window: 256K, compared with 200K.
Last updated August 7, 2026
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