ALLaM-2-7b vs MiniMax Text 01 (MiniMax) vs Qwen3-VL Plus
Qwen3-VL Plus comes out ahead, 57 to 39 and 0 on our weighted score, and it is the cheaper option too.
SDAIA
ALLaM-2-7b
0/100- ECI—
- Price—
- Context4K
MiniMaxMiniMax Text 01 (MiniMax)
39/100- ECI—
- Price—
- Context1M
- Our pick
Alibaba (Qwen)Qwen3-VL Plus
57/100- ECI—
- Price$0.20 / $1.60
- Context262K
Qwen3-VL Plus is our pick
Qwen3-VL Plus is the better all-round choice, scoring 57/100 against MiniMax Text 01 (MiniMax) (39) and ALLaM-2-7b (0). It leads on inputs & features. MiniMax Text 01 (MiniMax) wins on context window. 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 priceQwen3-VL PlusQwen3-VL Plus $0.55 per 1M tokens (3:1 blend) · ALLaM-2-7b and MiniMax Text 01 (MiniMax) unpriced
- Longest contextMiniMax Text 01 (MiniMax)MiniMax Text 01 (MiniMax) 1,000,000 · Qwen3-VL Plus 262,144 · ALLaM-2-7b 4,096 tokens
- Widest inputsQwen3-VL PlusALLaM-2-7b: Text · MiniMax Text 01 (MiniMax): Text · Qwen3-VL Plus: Text, Images
- Self-hostingALLaM-2-7bPublishes downloadable weights
| Measure | Weight | ALLaM-2-7b | MiniMax Text 01 (MiniMax) | Qwen3-VL Plus |
|---|---|---|---|---|
| Inputs & features | 60% | 0 | 25 | 70 |
| Context window | 40% | 0 | 60 | 37 |
| Overall | 100% | 0/100 | 39/100 | 57/100 |
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 | ALLaM-2-7bSDAIA | MiniMax Text 01 (MiniMax)MiniMax | Qwen3-VL PlusAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | — | $0.20 |
| Output | — | — | $1.60 |
| Cached input | — | — | $0.04 |
| Blended (3:1) | — | — | $0.55 |
| Long-context rate | — | — | Over 32K: $0.30 / $2.40 |
| Price source | — | — | Official Alibaba API |
| Limits | |||
| Context window | 4,096 tokens | 1,000,000 tokens (best) | 262,144 tokens |
| Max output | 4,096 tokens | 131,072 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | — | — | qwen3-vl-plus |
| API providers | 2 | — | 6 (best) |
| Released | Jan 23, 2025 | Jan 15, 2025 | Sep 23, 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.
- ALLaM-2-7b—
- MiniMax Text 01 (MiniMax)—
- Qwen3-VL Plus$5.20
Which should you choose?
Which is better: ALLaM-2-7b, MiniMax Text 01 (MiniMax) or Qwen3-VL Plus?
Qwen3-VL Plus is the better all-round choice, scoring 57/100 against MiniMax Text 01 (MiniMax) (39) and ALLaM-2-7b (0). It leads on inputs & features. MiniMax Text 01 (MiniMax) wins on context window. 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, ALLaM-2-7b, MiniMax Text 01 (MiniMax) or Qwen3-VL Plus?
Qwen3-VL Plus is cheaper at $0.20 input / $1.60 output per million tokens (official Alibaba API price). . At a typical mix of three input tokens to one output token, that is $0.55 per million tokens for Qwen3-VL Plus versus . ALLaM-2-7b and MiniMax Text 01 (MiniMax) has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. ALLaM-2-7b has not been scored yet, MiniMax Text 01 (MiniMax) has not been scored yet and Qwen3-VL Plus has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for ALLaM-2-7b, MiniMax Text 01 (MiniMax) and Qwen3-VL Plus 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 262,144 for Qwen3-VL Plus and 4,096 for ALLaM-2-7b. Maximum output per response: ALLaM-2-7b up to 4,096, MiniMax Text 01 (MiniMax) up to 131,072, Qwen3-VL Plus up to 32,768 tokens.
Which can read images, PDFs, audio or video?
ALLaM-2-7b accepts text; MiniMax Text 01 (MiniMax) accepts text; Qwen3-VL Plus accepts text and images. Qwen3-VL Plus handles the widest range of inputs.
Are any of these open source?
ALLaM-2-7b publishes its weights and can be self-hosted; MiniMax Text 01 (MiniMax) and Qwen3-VL Plus is proprietary.
Which is newer?
Qwen3-VL Plus is the newest, released Sep 23, 2025. ALLaM-2-7b came out Jan 23, 2025; MiniMax Text 01 (MiniMax) came out Jan 15, 2025. Knowledge cutoff: Qwen3-VL 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 Nov 2, 2026.
