DeepSeek V3 0324 vs MiniMax-M2.7 vs Qwen3 8B
MiniMax-M2.7 comes out ahead, 61 to 56 and 54 on our weighted score, though Qwen3 8B is 41% cheaper per token.
DeepSeek
DeepSeek V3 0324
54/100- ECI135.9
- Price$0.24 / $0.90
- Context164K
- Our pick
MiniMax
MiniMax-M2.7
61/100- ECI145.9
- Price$0.30 / $1.20
- Context205K
Alibaba (Qwen)
Qwen3 8B
56/100- ECI136.2
- Price$0.18 / $0.70
- Context131K
MiniMax-M2.7 is our pick
MiniMax-M2.7 is the better all-round choice, scoring 61/100 against Qwen3 8B (56) and DeepSeek V3 0324 (54). It leads on capability and context window. Qwen3 8B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMiniMax-M2.7Capabilities Index (ECI): MiniMax-M2.7 145.9 · Qwen3 8B 136.2 · DeepSeek V3 0324 135.9
- Lowest priceQwen3 8BQwen3 8B $0.31 · DeepSeek V3 0324 $0.405 · MiniMax-M2.7 $0.525 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M2.7MiniMax-M2.7 204,800 · DeepSeek V3 0324 163,840 · Qwen3 8B 131,072 tokens
- Widest inputsSame inputsDeepSeek V3 0324: Text · MiniMax-M2.7: Text · Qwen3 8B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek V3 0324 | MiniMax-M2.7 | Qwen3 8B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 60 | 73 | 61 |
| Price | 25% | 68 | 63 | 74 |
| Inputs & features | 15% | 25 | 35 | 35 |
| Context window | 10% | 28 | 32 | 24 |
| Overall | 100% | 54/100 | 61/100 | 56/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 135.9 | 145.9 (best) | 136.2 |
| ECI rank | #114 of 148 | #73 of 148 (best) | #113 of 148 |
| GPQA DiamondGraduate-level science questions | 67.6% (best) | — | 56.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 37.8% | — | 56.1% (best) |
| Price per million tokens | |||
| Input | $0.24 | $0.30 | $0.18 (best) |
| Output | $0.90 | $1.20 | $0.70 (best) |
| Cached input | — | $0.06 | — |
| Blended (3:1) | $0.405 | $0.525 | $0.31 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 5 providers | Official MiniMax (minimax.io) API | Official Alibaba API |
| Limits | |||
| Context window | 163,840 tokens | 204,800 tokens (best) | 131,072 tokens |
| Max output | 163,840 tokens (best) | 131,072 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | MiniMax-M2.7 | qwen3-8b |
| API providers | 5 | 29 (best) | 1 |
| Released | Mar 24, 2025 | Mar 18, 2026 | Apr 28, 2025 |
| Knowledge cutoff | — | — | Apr 2025 |
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 0324$4.20
MiniMax-M2.7$5.40
Qwen3 8B$3.20
Which should you choose?
Which is better: DeepSeek V3 0324, MiniMax-M2.7 or Qwen3 8B?
MiniMax-M2.7 is the better all-round choice, scoring 61/100 against Qwen3 8B (56) and DeepSeek V3 0324 (54). It leads on capability and context window. Qwen3 8B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek V3 0324, MiniMax-M2.7 or Qwen3 8B?
Qwen3 8B is cheaper at $0.18 input / $0.70 output per million tokens (official Alibaba API price). DeepSeek V3 0324 costs $0.24 input / $0.90 output per million tokens (median across 5 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 $0.31 per million tokens for Qwen3 8B versus $0.405 for DeepSeek V3 0324 (1.3× as much) and $0.525 for MiniMax-M2.7 (1.7× 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), Qwen3 8B 136.2 (#113 of 148) and DeepSeek V3 0324 135.9 (#114 of 148). Their confidence ranges do not overlap (138.2–148.0 vs 129.7–138.1), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V3 0324, MiniMax-M2.7 and Qwen3 8B 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. All three 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 163,840 for DeepSeek V3 0324 and 131,072 for Qwen3 8B. Maximum output per response: DeepSeek V3 0324 up to 163,840, MiniMax-M2.7 up to 131,072, Qwen3 8B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V3 0324 accepts text; MiniMax-M2.7 accepts text; Qwen3 8B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
MiniMax-M2.7 is the newest, released Mar 18, 2026. Qwen3 8B came out Apr 28, 2025; DeepSeek V3 0324 came out Mar 24, 2025. Knowledge cutoff: Qwen3 8B Apr 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.