Qwen3 VL 235B A22B Instruct vs Seed 1.6 vs MiniMax-M2
Too close to call on our weighted score (Seed 1.6 55, Qwen3 VL 235B A22B Instruct 53, MiniMax-M2 48). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3 VL 235B A22B Instruct
53/100- ECI—
- Price$0.30 / $1.55
- Context131K
ByteDance SeedSeed 1.6
55/100- ECI—
- Price$0.119 / $1.19
- Context256K
MiniMaxMiniMax-M2
48/100- ECI—
- Price$0.30 / $1.20
- Context205K
Too close to call
It is close. Our weighted score puts them within 3 points (Seed 1.6 55/100, Qwen3 VL 235B A22B Instruct 53/100, MiniMax-M2 48/100), so choose by what matters most for your work: Seed 1.6 on price and Seed 1.6 for long inputs. 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 priceSeed 1.6Seed 1.6 $0.386 · MiniMax-M2 $0.525 · Qwen3 VL 235B A22B Instruct $0.613 per 1M tokens (3:1 blend)
- Longest contextSeed 1.6Seed 1.6 256,000 · MiniMax-M2 204,800 · Qwen3 VL 235B A22B Instruct 131,072 tokens
- Widest inputsQwen3 VL 235B A22B InstructQwen3 VL 235B A22B Instruct: Text, Images · Seed 1.6: Text · MiniMax-M2: Text
- Self-hostingQwen3 VL 235B A22B Instruct and MiniMax-M2Publishes downloadable weights
| Measure | Weight | Qwen3 VL 235B A22B Instruct | Seed 1.6 | MiniMax-M2 |
|---|---|---|---|---|
| Price | 50% | 60 | 69 | 63 |
| Inputs & features | 30% | 60 | 45 | 35 |
| Context window | 20% | 24 | 36 | 32 |
| Overall | 100% | 53/100 | 55/100 | 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 VL 235B A22B InstructAlibaba (Qwen) | Seed 1.6ByteDance Seed | MiniMax-M2MiniMax |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.119 (best) | $0.30 |
| Output | $1.55 | $1.19 (best) | $1.20 |
| Cached input | — | $0.024 | — |
| Blended (3:1) | $0.613 | $0.386 (best) | $0.525 |
| Long-context rate | Same rate | Over 32K: $0.178 / $2.37 | Same rate |
| Price source | Median of 12 providers | Official Volcengine Ark API | Official MiniMax (minimax.io) API |
| Limits | |||
| Context window | 131,072 tokens | 256,000 tokens (best) | 204,800 tokens |
| Max output | 32,768 tokens | 64,000 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 | Yesminimal · low · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | — | doubao-seed-1-6-251015 | MiniMax-M2 |
| API providers | 12 | 2 | 13 (best) |
| Released | Sep 23, 2025 | Oct 15, 2025 | Oct 27, 2025 |
| Knowledge cutoff | Mar 31, 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
- Seed 1.6$3.56
- MiniMax-M2$5.40
Which should you choose?
Which is better: Qwen3 VL 235B A22B Instruct, Seed 1.6 or MiniMax-M2?
It is close. Our weighted score puts them within 3 points (Seed 1.6 55/100, Qwen3 VL 235B A22B Instruct 53/100, MiniMax-M2 48/100), so choose by what matters most for your work: Seed 1.6 on price and Seed 1.6 for long inputs. 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, Seed 1.6 or MiniMax-M2?
Seed 1.6 is cheaper at $0.119 input / $1.19 output per million tokens (official Volcengine Ark API price). MiniMax-M2 costs $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). At a typical mix of three input tokens to one output token, that is $0.386 per million tokens for Seed 1.6 versus $0.525 for MiniMax-M2 (1.4× as much) and $0.613 for Qwen3 VL 235B A22B Instruct (1.6× 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, Seed 1.6 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, Seed 1.6 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?
Seed 1.6 has the largest context window at 256,000 tokens, against 204,800 for MiniMax-M2 and 131,072 for Qwen3 VL 235B A22B Instruct. Maximum output per response: Qwen3 VL 235B A22B Instruct up to 32,768, Seed 1.6 up to 64,000, MiniMax-M2 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3 VL 235B A22B Instruct accepts text and images; Seed 1.6 accepts text; MiniMax-M2 accepts text. Qwen3 VL 235B A22B Instruct handles the widest range of inputs.
Are any of these open source?
Qwen3 VL 235B A22B Instruct and MiniMax-M2 publishes its weights and can be self-hosted; Seed 1.6 is proprietary.
Which is newer?
MiniMax-M2 is the newest, released Oct 27, 2025. Seed 1.6 came out Oct 15, 2025; Qwen3 VL 235B A22B Instruct came out Sep 23, 2025. Knowledge cutoff: Qwen3 VL 235B A22B Instruct Mar 31, 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.
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