Qwen MT Plus vs Gemini Robotics-ER 1.6 Preview vs GPT-5 Chat
Gemini Robotics-ER 1.6 Preview comes out ahead, 46 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 pick
Google
Gemini Robotics-ER 1.6 Preview
46/100- ECI—
- Price$1.00 / $5.00
- Context131K
OpenAI
GPT-5 Chat
31/100- ECI—
- Price$1.25 / $10.00
- Context400K
Gemini Robotics-ER 1.6 Preview is our pick
Gemini Robotics-ER 1.6 Preview is the better all-round choice, scoring 46/100 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 priceGemini Robotics-ER 1.6 PreviewGemini Robotics-ER 1.6 Preview $2.00 · GPT-5 Chat $3.44 · Qwen MT Plus $3.69 per 1M tokens (3:1 blend)
- Longest contextGPT-5 ChatGPT-5 Chat 400,000 · Gemini Robotics-ER 1.6 Preview 131,072 · Qwen MT Plus 16,384 tokens
- Widest inputsGemini Robotics-ER 1.6 PreviewQwen MT Plus: Text · Gemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video · GPT-5 Chat: Text, Images
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Qwen MT Plus | Gemini Robotics-ER 1.6 Preview | GPT-5 Chat |
|---|---|---|---|---|
| Price | 50% | 22 | 34 | 23 |
| Inputs & features | 30% | 0 | 80 | 35 |
| Context window | 20% | 0 | 25 | 44 |
| Overall | 100% | 11/100 | 46/100 | 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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.46 | $1.00 (best) | $1.25 |
| Output | $7.37 | $5.00 (best) | $10.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.69 | $2.00 (best) | $3.44 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 1 providers | Median of 5 providers |
| Limits | |||
| Context window | 16,384 tokens | 131,072 tokens | 400,000 tokens (best) |
| Max output | 8,192 tokens | 65,536 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | No | Yes | Yes |
| Tool calling | No | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | qwen-mt-plus | — | — |
| API providers | 3 | 1 | 5 (best) |
| Released | Jul 24, 2025 | Apr 14, 2026 | Aug 7, 2025 |
| Knowledge cutoff | — | Jan 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
Gemini Robotics-ER 1.6 Preview$20.00
GPT-5 Chat$32.50
Which should you choose?
Which is better: Qwen MT Plus, Gemini Robotics-ER 1.6 Preview or GPT-5 Chat?
Gemini Robotics-ER 1.6 Preview is the better all-round choice, scoring 46/100 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, Gemini Robotics-ER 1.6 Preview or GPT-5 Chat?
Gemini Robotics-ER 1.6 Preview is cheaper at $1.00 input / $5.00 output per million tokens (median across 1 API provider). 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 $2.00 per million tokens for Gemini Robotics-ER 1.6 Preview versus $3.44 for GPT-5 Chat (1.7× as much) and $3.69 for Qwen MT Plus (1.8× 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, Gemini Robotics-ER 1.6 Preview 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, Gemini Robotics-ER 1.6 Preview 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 Gemini Robotics-ER 1.6 Preview and 16,384 for Qwen MT Plus. Maximum output per response: Qwen MT Plus up to 8,192, Gemini Robotics-ER 1.6 Preview up to 65,536, GPT-5 Chat up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Qwen MT Plus accepts text; Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video; GPT-5 Chat accepts text and images. Gemini Robotics-ER 1.6 Preview handles the widest range of inputs.
Are any of these open source?
No. Qwen MT Plus, Gemini Robotics-ER 1.6 Preview and GPT-5 Chat are proprietary and only available through APIs and apps.
Which is newer?
Gemini Robotics-ER 1.6 Preview is the newest, released Apr 14, 2026. GPT-5 Chat came out Aug 7, 2025; Qwen MT Plus came out Jul 24, 2025. Knowledge cutoff: Gemini Robotics-ER 1.6 Preview Jan 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.