vs
1:5
overall capability wins (0 ties across 6 scored). MiniMax M2.7 leads overall.
- Reasoning0:4
- Coding0:1
- Specs1:0
Verdict
MiniMax M2.7 leads coding (widest gap: +12.0 on SciCode); Agnes-3.0-Flash Preview offers larger context (262K vs 205K); Agnes-3.0-Flash Preview ships open weights (Apache 2.0).
- MiniMax M2.7 leads coding (widest gap: +12.0 on SciCode)
- Agnes-3.0-Flash Preview offers larger context (262K vs 205K)
- Agnes-3.0-Flash Preview ships open weights (Apache 2.0)
Cost for 1M in + 250K out
Illustrative chat workload at primary-provider list prices.
- Agnes-3.0-Flash Preview
- -
- MiniMax M2.7
- $0.60
Price per 1M tokens
Full comparison
Organization
Agnes AI
MiniMax
Family
Other
Other
License
Apache 2.0
Proprietary
Open weights
Yes
No
Release
Sep 13, 2026
Mar 18, 2026
Knowledge cutoff
-
-
API / provider
No primary API price listed
MiniMax
Modalities
text, image, video → text
text, image → text
Specs
Context window
262K
205K
Max output
-
16K
Parameters
33B
—
Pricing
Input $/1M
—
$0.30
Output $/1M
—
$1.20
Blended $/1M (3∶1)
-
$0.52
Speed
tok/s
-
85
TTFT (s)
-
0.35
Reasoning
MMLU-Pro
—
—
GPQA Diamond
85.0
87.4
Humanity's Last Exam
—
29.6
AIME 2025
—
—
MATH-500
—
—
Humanity's Last Exam (with tools)
—
—
AA-Omniscience Accuracy
23.0
26.8
AA-LCR v1.1
68.3
78.3
CritPt
—
0.6
MMMU-Pro
—
—
IFBench
74.2
75.7
Chartography
—
—
Chartography (With Tools)
—
—
Coding
SWE-bench Verified
—
—
SWE-bench Pro
—
56.2
SWE-bench Multilingual
—
76.5
LiveCodeBench
—
—
Terminal-Bench 2.1
—
55.4
Aider Polyglot
—
—
Terminal-Bench 3
—
—
BigCodeBench
—
—
SciCode
38.1
50.1
CursorBench
—
—
SWE-Rebench
—
51.9
NL2Repo-Bench
—
39.8
DeepSWE
—
—
WebDev Arena
—
1,398
Terminal-Bench 4.0
—
—
CursorBench 4.0
—
—
FrontierCode v1.1 (Main)
—
—
Arena
LMArena Elo
—
1,415
| Metric | Agnes-3.0-Flash Preview | MiniMax M2.7 | Delta |
|---|---|---|---|
| Identity | |||
| Organization | Agnes AI | MiniMax | — |
| Family | Other | Other | — |
| License | Apache 2.0 | Proprietary | — |
| Open weights | Yes | No | — |
| Release | Sep 13, 2026 | Mar 18, 2026 | — |
| Knowledge cutoff | - | - | — |
| API / provider | No primary API price listed | MiniMax | — |
| Modalities | text, image, video → text | text, image → text | — |
| Specs | |||
| Context window | 262K | 205K | A +57K |
| Max output | - | 16K | — |
| Parameters | 33B | — | — |
| Pricing | |||
| Input $/1M | — | $0.30 | — |
| Output $/1M | — | $1.20 | — |
| Blended $/1M (3∶1) | - | $0.52 | — |
| Speed | |||
| tok/s | - | 85 | — |
| TTFT (s) | - | 0.35 | — |
| Reasoning | |||
| MMLU-Pro | — | — | — |
| GPQA Diamond | 85.0 | 87.4 | B +2.4 pts |
| Humanity's Last Exam | — | 29.6 | — |
| AIME 2025 | — | — | — |
| MATH-500 | — | — | — |
| Humanity's Last Exam (with tools) | — | — | — |
| AA-Omniscience Accuracy | 23.0 | 26.8 | B +3.8 pts |
| AA-LCR v1.1 | 68.3 | 78.3 | B +10.0 pts |
| CritPt | — | 0.6 | — |
| MMMU-Pro | — | — | — |
| IFBench | 74.2 | 75.7 | B +1.5 pts |
| Chartography | — | — | — |
| Chartography (With Tools) | — | — | — |
| Coding | |||
| SWE-bench Verified | — | — | — |
| SWE-bench Pro | — | 56.2 | — |
| SWE-bench Multilingual | — | 76.5 | — |
| LiveCodeBench | — | — | — |
| Terminal-Bench 2.1 | — | 55.4 | — |
| Aider Polyglot | — | — | — |
| Terminal-Bench 3 | — | — | — |
| BigCodeBench | — | — | — |
| SciCode | 38.1 | 50.1 | B +12.0 pts |
| CursorBench | — | — | — |
| SWE-Rebench | — | 51.9 | — |
| NL2Repo-Bench | — | 39.8 | — |
| DeepSWE | — | — | — |
| WebDev Arena | — | 1,398 | — |
| Terminal-Bench 4.0 | — | — | — |
| CursorBench 4.0 | — | — | — |
| FrontierCode v1.1 (Main) | — | — | — |
| Arena | |||
| LMArena Elo | — | 1,415 | — |
Agnes-3.0-Flash Preview
- Context
- 262K
- Parameters
- 33B
- Price
- —
- Speed
- —
- Modalities
- text, image, video → text
- License
- Apache 2.0
Agnes AI's (Sapiens AI, Singapore) first open-weight release: a 33B-parameter hybrid-attention model (54 gated delta-rule recurrent layers alternating with 18 global-attention layers, 3:1) under Apache 2.0, with a 262K-token context window and text/image/video input. This open-weight Preview checkpoint is distinct from Agnes AI's production "Agnes 3.0 Flash" API model, which runs a different checkpoint and is not open-weight; the two should not be conflated.
MiniMax M2.7
- Context
- 205K / 16K out
- Parameters
- —
- Price
- $0.30 / $1.20
- Speed
- 85 tok/s · 0.35s TTFT
- Modalities
- text, image → text
- License
- Proprietary
MiniMax M2.7 (Mar 2026) — prior coding-focused API flagship before M3; strong STEM and long-context multimodal chat.
Benchmark charts
Winner bars are emphasized. Per-benchmark deltas sit above each chart.