MiniMax-M2.7 vs DeepSeek V3.2
DeepSeek V3.2 comes out ahead, 64 to 61 on our weighted score, and it is the cheaper option too.
MiniMaxMiniMax-M2.7
61/100- ECI145.9
- Price$0.30 / $1.20
- Context205K
- Our pick
DeepSeekDeepSeek V3.2
64/100- ECI146.3
- Price$0.296 / $0.48
- Context128K
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Make it a three-way comparison.
DeepSeek V3.2 is our pick
DeepSeek V3.2 is the better all-round choice, scoring 64/100 against MiniMax-M2.7 (61). It leads on price and inputs & features. MiniMax-M2.7 wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek V3.2Capabilities Index (ECI): DeepSeek V3.2 146.3 · MiniMax-M2.7 145.9
- Lowest priceDeepSeek V3.2DeepSeek V3.2 $0.342 · MiniMax-M2.7 $0.525 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M2.7MiniMax-M2.7 204,800 · DeepSeek V3.2 128,000 tokens
- Widest inputsSame inputsMiniMax-M2.7: Text · DeepSeek V3.2: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | MiniMax-M2.7 | DeepSeek V3.2 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 73 | 73 |
| Price | 25% | 63 | 72 |
| Inputs & features | 15% | 35 | 45 |
| Context window | 10% | 32 | 24 |
| Overall | 100% | 61/100 | 64/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | MiniMax-M2.7MiniMax | DeepSeek V3.2DeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 145.9 | 146.3 (best) |
| ECI rank | #73 of 148 | #69 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | 83.4% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 87.8% |
| Price per million tokens | ||
| Input | $0.30 | $0.296 (best) |
| Output | $1.20 | $0.48 (best) |
| Cached input | $0.06 | — |
| Blended (3:1) | $0.525 | $0.342 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Median of 15 providers |
| Limits | ||
| Context window | 204,800 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 64,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Open | OpenMIT License |
| API model ID | MiniMax-M2.7 | — |
| API providers | 29 (best) | 15 |
| Released | Mar 18, 2026 | Dec 1, 2025 |
| Knowledge cutoff | — | Jul 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- MiniMax-M2.7$5.40
- DeepSeek V3.2$3.92
Which should you choose?
Which is better: MiniMax-M2.7 or DeepSeek V3.2?
DeepSeek V3.2 is the better all-round choice, scoring 64/100 against MiniMax-M2.7 (61). It leads on price and inputs & features. MiniMax-M2.7 wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, MiniMax-M2.7 or DeepSeek V3.2?
DeepSeek V3.2 is cheaper at $0.296 input / $0.48 output per million tokens (median across 15 API providers). MiniMax-M2.7 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $0.342 per million tokens for DeepSeek V3.2 versus $0.525 for MiniMax-M2.7 (1.5× as much).
Which scores higher on benchmarks?
DeepSeek V3.2 scores higher on the Capabilities Index (ECI): DeepSeek V3.2 146.3 (#69 of 148) and MiniMax-M2.7 145.9 (#73 of 148). The confidence ranges of the top two overlap (144.4–147.5 vs 138.2–148.0), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2.7 and DeepSeek V3.2 yet, so there is no like-for-like coding score. On overall capability, DeepSeek V3.2 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
MiniMax-M2.7 has the largest context window at 204,800 tokens, against 128,000 for DeepSeek V3.2. Maximum output per response: MiniMax-M2.7 up to 131,072, DeepSeek V3.2 up to 64,000 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.7 accepts text; DeepSeek V3.2 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (MIT License), so you can self-host them.
Which is newer?
MiniMax-M2.7 is the newest, released Mar 18, 2026. DeepSeek V3.2 came out Dec 1, 2025. Knowledge cutoff: DeepSeek V3.2 Jul 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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