Qwen3.5 Plus vs DeepSeek OCR 2 vs MiniMax-M2.5
Qwen3.5 Plus comes out ahead, 59 to 48 and 32 on our weighted score, though MiniMax-M2.5 is 42% cheaper per token.
- Our pick
Alibaba (Qwen)Qwen3.5 Plus
59/100- ECI146.8
- Price$0.40 / $2.40
- Context1M
DeepSeekDeepSeek OCR 2
32/100- ECI—
- Price$0.89 / $1.47
- Context8K
MiniMaxMiniMax-M2.5
48/100- ECI146.7
- Price$0.30 / $1.20
- Context205K
Qwen3.5 Plus is our pick
Qwen3.5 Plus is the better all-round choice, scoring 59/100 against MiniMax-M2.5 (48) and DeepSeek OCR 2 (32). It leads on inputs & features and context window. MiniMax-M2.5 wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceMiniMax-M2.5MiniMax-M2.5 $0.525 · Qwen3.5 Plus $0.90 · DeepSeek OCR 2 $1.03 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 PlusQwen3.5 Plus 1,000,000 · MiniMax-M2.5 204,800 · DeepSeek OCR 2 8,192 tokens
- Widest inputsQwen3.5 PlusQwen3.5 Plus: Text, Images, Video · DeepSeek OCR 2: Text, Images · MiniMax-M2.5: Text
- Self-hostingDeepSeek OCR 2 and MiniMax-M2.5Publishes downloadable weights
| Measure | Weight | Qwen3.5 Plus | DeepSeek OCR 2 | MiniMax-M2.5 |
|---|---|---|---|---|
| Price | 50% | 52 | 49 | 63 |
| Inputs & features | 30% | 70 | 25 | 35 |
| Context window | 20% | 60 | 0 | 32 |
| Overall | 100% | 59/100 | 32/100 | 48/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.5 PlusAlibaba (Qwen) | DeepSeek OCR 2DeepSeek | MiniMax-M2.5MiniMax |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 146.8 (best) | — | 146.7 |
| ECI rank | #65 of 148 (best) | — | #66 of 148 |
| GPQA DiamondGraduate-level science questions | 84.9% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 86.7% | — | — |
| SimpleQA VerifiedShort factual questions | 25.4% | — | — |
| Price per million tokens | |||
| Input | $0.40 | $0.89 | $0.30 (best) |
| Output | $2.40 | $1.47 | $1.20 (best) |
| Cached input | — | — | $0.03 |
| Blended (3:1) | $0.90 | $1.03 | $0.525 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 1 providers | Official MiniMax (minimax.io) API |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 8,192 tokens | 204,800 tokens |
| Max output | 65,536 tokens | 8,192 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | qwen3.5-plus | — | MiniMax-M2.5 |
| API providers | 10 | 2 | 21 (best) |
| Released | Feb 16, 2026 | Jan 27, 2026 | Feb 12, 2026 |
| 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.
- Qwen3.5 Plus$8.80
- DeepSeek OCR 2$11.83
- MiniMax-M2.5$5.40
Which should you choose?
Which is better: Qwen3.5 Plus, DeepSeek OCR 2 or MiniMax-M2.5?
Qwen3.5 Plus is the better all-round choice, scoring 59/100 against MiniMax-M2.5 (48) and DeepSeek OCR 2 (32). It leads on inputs & features and context window. MiniMax-M2.5 wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Qwen3.5 Plus, DeepSeek OCR 2 or MiniMax-M2.5?
MiniMax-M2.5 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). Qwen3.5 Plus costs $0.40 input / $2.40 output per million tokens (official Alibaba API price); DeepSeek OCR 2 costs $0.89 input / $1.47 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for MiniMax-M2.5 versus $0.90 for Qwen3.5 Plus (1.7× as much) and $1.03 for DeepSeek OCR 2 (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.5 Plus has an ECI of 146.8, DeepSeek OCR 2 has not been scored yet and MiniMax-M2.5 has an ECI of 146.7.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 Plus, DeepSeek OCR 2 and MiniMax-M2.5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that DeepSeek OCR 2 does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen3.5 Plus has the largest context window at 1,000,000 tokens, against 204,800 for MiniMax-M2.5 and 8,192 for DeepSeek OCR 2. Maximum output per response: Qwen3.5 Plus up to 65,536, DeepSeek OCR 2 up to 8,192, MiniMax-M2.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3.5 Plus accepts text, images and video; DeepSeek OCR 2 accepts text and images; MiniMax-M2.5 accepts text. Qwen3.5 Plus handles the widest range of inputs.
Are any of these open source?
DeepSeek OCR 2 and MiniMax-M2.5 publishes its weights and can be self-hosted; Qwen3.5 Plus is proprietary.
Which is newer?
Qwen3.5 Plus is the newest, released Feb 16, 2026. MiniMax-M2.5 came out Feb 12, 2026; DeepSeek OCR 2 came out Jan 27, 2026. Knowledge cutoff: Qwen3.5 Plus 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.
