DeepSeek OCR 2 vs GLM-4.7 vs MiniMax-M2.5-highspeed
Too close to call on our weighted score (GLM-4.7 42, MiniMax-M2.5-highspeed 41, DeepSeek OCR 2 32). The right pick depends on what you value most.
DeepSeekDeepSeek OCR 2
32/100- ECI—
- Price$0.89 / $1.47
- Context8K
Z.ai (Zhipu)GLM-4.7
42/100- ECI143.5
- Price$0.60 / $2.20
- Context205K
MiniMaxMiniMax-M2.5-highspeed
41/100- ECI—
- Price$0.60 / $2.40
- Context205K
Too close to call
It is close. Our weighted score puts them within a point (GLM-4.7 42/100, MiniMax-M2.5-highspeed 41/100, DeepSeek OCR 2 32/100), so choose by what matters most for your work: GLM-4.7 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 priceGLM-4.7GLM-4.7 $1.00 · DeepSeek OCR 2 $1.03 · MiniMax-M2.5-highspeed $1.05 per 1M tokens (3:1 blend)
- Longest contextGLM-4.7 and MiniMax-M2.5-highspeedGLM-4.7 204,800 · MiniMax-M2.5-highspeed 204,800 · DeepSeek OCR 2 8,192 tokens
- Widest inputsDeepSeek OCR 2DeepSeek OCR 2: Text, Images · GLM-4.7: Text · MiniMax-M2.5-highspeed: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek OCR 2 | GLM-4.7 | MiniMax-M2.5-highspeed |
|---|---|---|---|---|
| Price | 50% | 49 | 50 | 49 |
| Inputs & features | 30% | 25 | 35 | 35 |
| Context window | 20% | 0 | 32 | 32 |
| Overall | 100% | 32/100 | 42/100 | 41/100 |
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 | DeepSeek OCR 2DeepSeek | GLM-4.7Z.ai (Zhipu) | MiniMax-M2.5-highspeedMiniMax |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 143.5 | — |
| ECI rank | — | #84 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 83.3% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 83.3% | — |
| SimpleQA VerifiedShort factual questions | — | 32.2% | — |
| Price per million tokens | |||
| Input | $0.89 | $0.60 (best) | $0.60 (best) |
| Output | $1.47 (best) | $2.20 | $2.40 |
| Cached input | — | $0.11 | $0.06 (best) |
| Blended (3:1) | $1.03 | $1.00 (best) | $1.05 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Z.AI API | Official MiniMax (minimax.io) API |
| Limits | |||
| Context window | 8,192 tokens | 204,800 tokens (best) | 204,800 tokens (best) |
| Max output | 8,192 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | glm-4.7 | MiniMax-M2.5-highspeed |
| API providers | 2 | 20 (best) | 7 |
| Released | Jan 27, 2026 | Dec 22, 2025 | Feb 13, 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.
- DeepSeek OCR 2$11.83
- GLM-4.7$10.40
- MiniMax-M2.5-highspeed$10.80
Which should you choose?
Which is better: DeepSeek OCR 2, GLM-4.7 or MiniMax-M2.5-highspeed?
It is close. Our weighted score puts them within a point (GLM-4.7 42/100, MiniMax-M2.5-highspeed 41/100, DeepSeek OCR 2 32/100), so choose by what matters most for your work: GLM-4.7 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, DeepSeek OCR 2, GLM-4.7 or MiniMax-M2.5-highspeed?
GLM-4.7 is cheaper at $0.60 input / $2.20 output per million tokens (official Z.AI API price). DeepSeek OCR 2 costs $0.89 input / $1.47 output per million tokens (median across 1 API provider); MiniMax-M2.5-highspeed costs $0.60 input / $2.40 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for GLM-4.7 versus $1.03 for DeepSeek OCR 2 (1× as much) and $1.05 for MiniMax-M2.5-highspeed (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DeepSeek OCR 2 has not been scored yet, GLM-4.7 has an ECI of 143.5 and MiniMax-M2.5-highspeed has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek OCR 2, GLM-4.7 and MiniMax-M2.5-highspeed 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?
GLM-4.7 and MiniMax-M2.5-highspeed have the largest context windows (204,800 and 204,800 tokens), against 8,192 for DeepSeek OCR 2. Maximum output per response: DeepSeek OCR 2 up to 8,192, GLM-4.7 up to 131,072, MiniMax-M2.5-highspeed up to 131,072 tokens.
Which can read images, PDFs, audio or video?
DeepSeek OCR 2 accepts text and images; GLM-4.7 accepts text; MiniMax-M2.5-highspeed accepts text. DeepSeek OCR 2 handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
MiniMax-M2.5-highspeed is the newest, released Feb 13, 2026. DeepSeek OCR 2 came out Jan 27, 2026; GLM-4.7 came out Dec 22, 2025. Knowledge cutoff: GLM-4.7 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.
