DeepSeek-V3.1 vs MiniMax-M2.7
MiniMax-M2.7 comes out ahead, 61 to 55 on our weighted score, and it is the cheaper option too.
DeepSeekDeepSeek-V3.1
55/100- ECI139.9
- Price$0.385 / $1.25
- Context131K
- Our pick
MiniMaxMiniMax-M2.7
61/100- ECI145.9
- Price$0.30 / $1.20
- Context205K
Add a model
Make it a three-way comparison.
MiniMax-M2.7 is our pick
MiniMax-M2.7 is the better all-round choice, scoring 61/100 against DeepSeek-V3.1 (55). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMiniMax-M2.7Capabilities Index (ECI): MiniMax-M2.7 145.9 · DeepSeek-V3.1 139.9
- Lowest priceMiniMax-M2.7MiniMax-M2.7 $0.525 · DeepSeek-V3.1 $0.601 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M2.7MiniMax-M2.7 204,800 · DeepSeek-V3.1 131,072 tokens
- Widest inputsSame inputsDeepSeek-V3.1: Text · MiniMax-M2.7: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-V3.1 | MiniMax-M2.7 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 65 | 73 |
| Price | 25% | 60 | 63 |
| Inputs & features | 15% | 35 | 35 |
| Context window | 10% | 24 | 32 |
| Overall | 100% | 55/100 | 61/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-V3.1DeepSeek | MiniMax-M2.7MiniMax |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 139.9 | 145.9 (best) |
| ECI rank | #100 of 148 | #73 of 148 (best) |
| Price per million tokens | ||
| Input | $0.385 | $0.30 (best) |
| Output | $1.25 | $1.20 (best) |
| Cached input | — | $0.06 |
| Blended (3:1) | $0.601 | $0.525 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 8 providers | Official MiniMax (minimax.io) API |
| Limits | ||
| Context window | 131,072 tokens | 204,800 tokens (best) |
| Max output | 8,192 tokens | 131,072 tokens (best) |
| 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 | No |
| Availability | ||
| Weights | OpenMIT License | Open |
| API model ID | — | MiniMax-M2.7 |
| API providers | 8 | 29 (best) |
| Released | Aug 21, 2025 | Mar 18, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek-V3.1$6.35
- MiniMax-M2.7$5.40
Which should you choose?
Which is better: DeepSeek-V3.1 or MiniMax-M2.7?
MiniMax-M2.7 is the better all-round choice, scoring 61/100 against DeepSeek-V3.1 (55). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-V3.1 or MiniMax-M2.7?
MiniMax-M2.7 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). DeepSeek-V3.1 costs $0.385 input / $1.25 output per million tokens (median across 8 API providers). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for MiniMax-M2.7 versus $0.601 for DeepSeek-V3.1 (1.1× as much).
Which scores higher on benchmarks?
MiniMax-M2.7 scores higher on the Capabilities Index (ECI): MiniMax-M2.7 145.9 (#73 of 148) and DeepSeek-V3.1 139.9 (#100 of 148). The confidence ranges of the top two overlap (138.2–148.0 vs 136.1–143.3), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-V3.1 and MiniMax-M2.7 yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.7 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 131,072 for DeepSeek-V3.1. Maximum output per response: DeepSeek-V3.1 up to 8,192, MiniMax-M2.7 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-V3.1 accepts text; MiniMax-M2.7 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-V3.1 came out Aug 21, 2025.
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.
Related comparisons
- Add Qwen3 14BThree-way comparison
- DeepSeek-V3.1 vs Qwen3 14BAlibaba (Qwen) · ECI 138.2
- DeepSeek-V3.1 vs Gemini 2.5 FlashGoogle · ECI 140.8
- DeepSeek-V3.1 vs GPT OSS 120BOpenAI · ECI 140.0
- DeepSeek-V3.1 vs GLM-4.7Z.ai (Zhipu) · ECI 143.5
- MiniMax-M2.7 vs GPT-5.4 nanoOpenAI · ECI 145.8
- MiniMax-M2.7 vs Qwen3.6 35B-A3BAlibaba (Qwen) · ECI 143.9
