Qwen3 VL 235B A22B Instruct vs Qwen3-Next 80B-A3B Instruct vs MiniMax-M2
Qwen3 VL 235B A22B Instruct comes out ahead, 53 to 48 and 39 on our weighted score, though MiniMax-M2 is 14% cheaper per token.
- Our pick
Alibaba (Qwen)
Qwen3 VL 235B A22B Instruct
53/100- ECI—
- Price$0.30 / $1.55
- Context131K
Alibaba (Qwen)
Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
MiniMax
MiniMax-M2
48/100- ECI—
- Price$0.30 / $1.20
- Context205K
Qwen3 VL 235B A22B Instruct is our pick
Qwen3 VL 235B A22B Instruct is the better all-round choice, scoring 53/100 against MiniMax-M2 (48) and Qwen3-Next 80B-A3B Instruct (39). It leads on inputs & features. MiniMax-M2 wins on price and context window. 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-M2MiniMax-M2 $0.525 · Qwen3 VL 235B A22B Instruct $0.613 · Qwen3-Next 80B-A3B Instruct $0.875 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M2MiniMax-M2 204,800 · Qwen3 VL 235B A22B Instruct 131,072 · Qwen3-Next 80B-A3B Instruct 131,072 tokens
- Widest inputsQwen3 VL 235B A22B InstructQwen3 VL 235B A22B Instruct: Text, Images · Qwen3-Next 80B-A3B Instruct: Text · MiniMax-M2: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 VL 235B A22B Instruct | Qwen3-Next 80B-A3B Instruct | MiniMax-M2 |
|---|---|---|---|---|
| Price | 50% | 60 | 53 | 63 |
| Inputs & features | 30% | 60 | 25 | 35 |
| Context window | 20% | 24 | 24 | 32 |
| Overall | 100% | 53/100 | 39/100 | 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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 (best) | $0.50 | $0.30 (best) |
| Output | $1.55 | $2.00 | $1.20 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.613 | $0.875 | $0.525 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 12 providers | Official Alibaba API | Official MiniMax (minimax.io) API |
| Limits | |||
| Context window | 131,072 tokens | 131,072 tokens | 204,800 tokens (best) |
| Max output | 32,768 tokens | 32,768 tokens | 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 | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | qwen3-next-80b-a3b-instruct | MiniMax-M2 |
| API providers | 12 | 13 (best) | 13 (best) |
| Released | Sep 23, 2025 | Sep 2025 | Oct 27, 2025 |
| Knowledge cutoff | Mar 31, 2025 | 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 VL 235B A22B Instruct$6.10
Qwen3-Next 80B-A3B Instruct$9.00
MiniMax-M2$5.40
Which should you choose?
Which is better: Qwen3 VL 235B A22B Instruct, Qwen3-Next 80B-A3B Instruct or MiniMax-M2?
Qwen3 VL 235B A22B Instruct is the better all-round choice, scoring 53/100 against MiniMax-M2 (48) and Qwen3-Next 80B-A3B Instruct (39). It leads on inputs & features. MiniMax-M2 wins on price and context window. 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 VL 235B A22B Instruct, Qwen3-Next 80B-A3B Instruct or MiniMax-M2?
MiniMax-M2 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). Qwen3 VL 235B A22B Instruct costs $0.30 input / $1.55 output per million tokens (median across 12 API providers); Qwen3-Next 80B-A3B Instruct costs $0.50 input / $2.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for MiniMax-M2 versus $0.613 for Qwen3 VL 235B A22B Instruct (1.2× as much) and $0.875 for Qwen3-Next 80B-A3B Instruct (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3 VL 235B A22B Instruct has not been scored yet, Qwen3-Next 80B-A3B Instruct has not been scored yet and MiniMax-M2 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 VL 235B A22B Instruct, Qwen3-Next 80B-A3B Instruct and MiniMax-M2 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
MiniMax-M2 has the largest context window at 204,800 tokens, against 131,072 for Qwen3 VL 235B A22B Instruct and 131,072 for Qwen3-Next 80B-A3B Instruct. Maximum output per response: Qwen3 VL 235B A22B Instruct up to 32,768, Qwen3-Next 80B-A3B Instruct up to 32,768, MiniMax-M2 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3 VL 235B A22B Instruct accepts text and images; Qwen3-Next 80B-A3B Instruct accepts text; MiniMax-M2 accepts text. Qwen3 VL 235B A22B Instruct 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 is the newest, released Oct 27, 2025. Qwen3 VL 235B A22B Instruct came out Sep 23, 2025; Qwen3-Next 80B-A3B Instruct came out Sep 2025. Knowledge cutoff: Qwen3 VL 235B A22B Instruct Mar 31, 2025, Qwen3-Next 80B-A3B Instruct 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.