Qwen MT Plus vs Qwen3 VL 235B A22B Thinking vs GPT-5 Chat
Qwen3 VL 235B A22B Thinking comes out ahead, 44 to 31 and 11 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen MT Plus
11/100- ECI—
- Price$2.46 / $7.37
- Context16K
- Our pickAlibaba (Qwen)
Qwen3 VL 235B A22B Thinking
44/100- ECI—
- Price$0.50 / $3.95
- Context131K
OpenAIGPT-5 Chat
31/100- ECI—
- Price$1.25 / $10.00
- Context400K
Qwen3 VL 235B A22B Thinking is our pick
Qwen3 VL 235B A22B Thinking is the better all-round choice, scoring 44/100 against GPT-5 Chat (31) and Qwen MT Plus (11). It leads on price and inputs & features. GPT-5 Chat wins on 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 priceQwen3 VL 235B A22B ThinkingQwen3 VL 235B A22B Thinking $1.36 · GPT-5 Chat $3.44 · Qwen MT Plus $3.69 per 1M tokens (3:1 blend)
- Longest contextGPT-5 ChatGPT-5 Chat 400,000 · Qwen3 VL 235B A22B Thinking 131,072 · Qwen MT Plus 16,384 tokens
- Widest inputsQwen3 VL 235B A22B Thinking and GPT-5 ChatQwen MT Plus: Text · Qwen3 VL 235B A22B Thinking: Text, Images · GPT-5 Chat: Text, Images
- Self-hostingQwen3 VL 235B A22B ThinkingPublishes downloadable weights
| Measure | Weight | Qwen MT Plus | Qwen3 VL 235B A22B Thinking | GPT-5 Chat |
|---|---|---|---|---|
| Price | 50% | 22 | 42 | 23 |
| Inputs & features | 30% | 0 | 60 | 35 |
| Context window | 20% | 0 | 25 | 44 |
| Overall | 100% | 11/100 | 44/100 | 31/100 |
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 | Qwen MT PlusAlibaba (Qwen) | Qwen3 VL 235B A22B ThinkingAlibaba (Qwen) | GPT-5 ChatOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.46 | $0.50 (best) | $1.25 |
| Output | $7.37 | $3.95 (best) | $10.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.69 | $1.36 (best) | $3.44 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 5 providers | Median of 5 providers |
| Limits | |||
| Context window | 16,384 tokens | 131,072 tokens | 400,000 tokens (best) |
| Max output | 8,192 tokens | 32,768 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | No | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | qwen-mt-plus | — | — |
| API providers | 3 | 5 (best) | 5 (best) |
| Released | Jul 24, 2025 | Sep 23, 2025 | Aug 7, 2025 |
| Knowledge cutoff | — | Mar 31, 2025 | Sep 30, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen MT Plus$39.34
- Qwen3 VL 235B A22B Thinking$12.90
- GPT-5 Chat$32.50
Which should you choose?
Which is better: Qwen MT Plus, Qwen3 VL 235B A22B Thinking or GPT-5 Chat?
Qwen3 VL 235B A22B Thinking is the better all-round choice, scoring 44/100 against GPT-5 Chat (31) and Qwen MT Plus (11). It leads on price and inputs & features. GPT-5 Chat wins on 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, Qwen MT Plus, Qwen3 VL 235B A22B Thinking or GPT-5 Chat?
Qwen3 VL 235B A22B Thinking is cheaper at $0.50 input / $3.95 output per million tokens (median across 5 API providers). GPT-5 Chat costs $1.25 input / $10.00 output per million tokens (median across 5 API providers); Qwen MT Plus costs $2.46 input / $7.37 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $1.36 per million tokens for Qwen3 VL 235B A22B Thinking versus $3.44 for GPT-5 Chat (2.5× as much) and $3.69 for Qwen MT Plus (2.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen MT Plus has not been scored yet, Qwen3 VL 235B A22B Thinking has not been scored yet and GPT-5 Chat has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen MT Plus, Qwen3 VL 235B A22B Thinking and GPT-5 Chat yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen MT Plus and GPT-5 Chat does not support tool calling, which most coding agents need.
Which has the bigger context window?
GPT-5 Chat has the largest context window at 400,000 tokens, against 131,072 for Qwen3 VL 235B A22B Thinking and 16,384 for Qwen MT Plus. Maximum output per response: Qwen MT Plus up to 8,192, Qwen3 VL 235B A22B Thinking up to 32,768, GPT-5 Chat up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Qwen MT Plus accepts text; Qwen3 VL 235B A22B Thinking accepts text and images; GPT-5 Chat accepts text and images. Qwen3 VL 235B A22B Thinking handles the widest range of inputs.
Are any of these open source?
Qwen3 VL 235B A22B Thinking publishes its weights and can be self-hosted; Qwen MT Plus and GPT-5 Chat is proprietary.
Which is newer?
Qwen3 VL 235B A22B Thinking is the newest, released Sep 23, 2025. GPT-5 Chat came out Aug 7, 2025; Qwen MT Plus came out Jul 24, 2025. Knowledge cutoff: Qwen3 VL 235B A22B Thinking Mar 31, 2025, GPT-5 Chat Sep 30, 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.
