MiniMax Text 01 (MiniMax) vs Qwen2.5-VL 72B Instruct vs ALLaM-2-7b
Too close to call on our weighted score (Qwen2.5-VL 72B Instruct 40, MiniMax Text 01 (MiniMax) 39, ALLaM-2-7b 0). The right pick depends on what you value most.
MiniMaxMiniMax Text 01 (MiniMax)
39/100- ECI—
- Price—
- Context1M
Alibaba (Qwen)Qwen2.5-VL 72B Instruct
40/100- ECI—
- Price$0.905 / $1.00
- Context131K
SDAIA
ALLaM-2-7b
0/100- ECI—
- Price—
- Context4K
Too close to call
It is close. Our weighted score puts them within a point (Qwen2.5-VL 72B Instruct 40/100, MiniMax Text 01 (MiniMax) 39/100, ALLaM-2-7b 0/100), so choose by what matters most for your work: Qwen2.5-VL 72B Instruct on price and MiniMax Text 01 (MiniMax) for long inputs. The score weighs inputs & features 60%, context window 40%. 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 priceQwen2.5-VL 72B InstructQwen2.5-VL 72B Instruct $0.93 per 1M tokens (3:1 blend) · MiniMax Text 01 (MiniMax) and ALLaM-2-7b unpriced
- Longest contextMiniMax Text 01 (MiniMax)MiniMax Text 01 (MiniMax) 1,000,000 · Qwen2.5-VL 72B Instruct 131,072 · ALLaM-2-7b 4,096 tokens
- Widest inputsQwen2.5-VL 72B InstructMiniMax Text 01 (MiniMax): Text · Qwen2.5-VL 72B Instruct: Text, Images · ALLaM-2-7b: Text
- Self-hostingQwen2.5-VL 72B Instruct and ALLaM-2-7bPublishes downloadable weights
| Measure | Weight | MiniMax Text 01 (MiniMax) | Qwen2.5-VL 72B Instruct | ALLaM-2-7b |
|---|---|---|---|---|
| Inputs & features | 60% | 25 | 50 | 0 |
| Context window | 40% | 60 | 25 | 0 |
| Overall | 100% | 39/100 | 40/100 | 0/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | MiniMax Text 01 (MiniMax)MiniMax | Qwen2.5-VL 72B InstructAlibaba (Qwen) | ALLaM-2-7bSDAIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $0.905 | — |
| Output | — | $1.00 | — |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.93 | — |
| Long-context rate | — | Same rate | — |
| Price source | — | Median of 6 providers | — |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 131,072 tokens | 4,096 tokens |
| Max output | 131,072 tokens (best) | 8,192 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | — | — |
| API providers | — | 6 (best) | 2 |
| Released | Jan 15, 2025 | Jan 26, 2025 | Jan 23, 2025 |
| Knowledge cutoff | — | Apr 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 Text 01 (MiniMax)—
- Qwen2.5-VL 72B Instruct$11.06
- ALLaM-2-7b—
Which should you choose?
Which is better: MiniMax Text 01 (MiniMax), Qwen2.5-VL 72B Instruct or ALLaM-2-7b?
It is close. Our weighted score puts them within a point (Qwen2.5-VL 72B Instruct 40/100, MiniMax Text 01 (MiniMax) 39/100, ALLaM-2-7b 0/100), so choose by what matters most for your work: Qwen2.5-VL 72B Instruct on price and MiniMax Text 01 (MiniMax) for long inputs. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, MiniMax Text 01 (MiniMax), Qwen2.5-VL 72B Instruct or ALLaM-2-7b?
Qwen2.5-VL 72B Instruct is cheaper at $0.905 input / $1.00 output per million tokens (median across 6 API providers). . At a typical mix of three input tokens to one output token, that is $0.93 per million tokens for Qwen2.5-VL 72B Instruct versus . MiniMax Text 01 (MiniMax) and ALLaM-2-7b has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax Text 01 (MiniMax) has not been scored yet, Qwen2.5-VL 72B Instruct has not been scored yet and ALLaM-2-7b has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax Text 01 (MiniMax), Qwen2.5-VL 72B Instruct and ALLaM-2-7b yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that ALLaM-2-7b does not support tool calling, which most coding agents need.
Which has the bigger context window?
MiniMax Text 01 (MiniMax) has the largest context window at 1,000,000 tokens, against 131,072 for Qwen2.5-VL 72B Instruct and 4,096 for ALLaM-2-7b. Maximum output per response: MiniMax Text 01 (MiniMax) up to 131,072, Qwen2.5-VL 72B Instruct up to 8,192, ALLaM-2-7b up to 4,096 tokens.
Which can read images, PDFs, audio or video?
MiniMax Text 01 (MiniMax) accepts text; Qwen2.5-VL 72B Instruct accepts text and images; ALLaM-2-7b accepts text. Qwen2.5-VL 72B Instruct handles the widest range of inputs.
Are any of these open source?
Qwen2.5-VL 72B Instruct and ALLaM-2-7b publishes its weights and can be self-hosted; MiniMax Text 01 (MiniMax) is proprietary.
Which is newer?
Qwen2.5-VL 72B Instruct is the newest, released Jan 26, 2025. ALLaM-2-7b came out Jan 23, 2025; MiniMax Text 01 (MiniMax) came out Jan 15, 2025. Knowledge cutoff: Qwen2.5-VL 72B Instruct Apr 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 Nov 2, 2026.
