Gemini Robotics-ER 1.6 Preview vs GPT-5 Chat vs Qwen MT Plus
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.
- 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
Alibaba (Qwen)
Qwen MT Plus
11/100- ECI—
- Price$2.46 / $7.37
- Context16K
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 PreviewGemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video · GPT-5 Chat: Text, Images · Qwen MT Plus: Text
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Gemini Robotics-ER 1.6 Preview | GPT-5 Chat | Qwen MT Plus |
|---|---|---|---|---|
| Price | 50% | 34 | 23 | 22 |
| Inputs & features | 30% | 80 | 35 | 0 |
| Context window | 20% | 25 | 44 | 0 |
| Overall | 100% | 46/100 | 31/100 | 11/100 |
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 | $1.00 (best) | $1.25 | $2.46 |
| Output | $5.00 (best) | $10.00 | $7.37 |
| Cached input | — | — | — |
| Blended (3:1) | $2.00 (best) | $3.44 | $3.69 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 5 providers | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens | 400,000 tokens (best) | 16,384 tokens |
| Max output | 65,536 tokens | 128,000 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | No | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | — | — | qwen-mt-plus |
| API providers | 1 | 5 (best) | 3 |
| Released | Apr 14, 2026 | Aug 7, 2025 | Jul 24, 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.
Gemini Robotics-ER 1.6 Preview$20.00
GPT-5 Chat$32.50
Qwen MT Plus$39.34
Which should you choose?
Which is better: Gemini Robotics-ER 1.6 Preview, GPT-5 Chat or Qwen MT Plus?
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, Gemini Robotics-ER 1.6 Preview, GPT-5 Chat or Qwen MT Plus?
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. Gemini Robotics-ER 1.6 Preview has not been scored yet, GPT-5 Chat has not been scored yet and Qwen MT Plus has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini Robotics-ER 1.6 Preview, GPT-5 Chat and Qwen MT Plus yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that GPT-5 Chat and Qwen MT Plus 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: Gemini Robotics-ER 1.6 Preview up to 65,536, GPT-5 Chat up to 128,000, Qwen MT Plus up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video; GPT-5 Chat accepts text and images; Qwen MT Plus accepts text. Gemini Robotics-ER 1.6 Preview handles the widest range of inputs.
Are any of these open source?
No. Gemini Robotics-ER 1.6 Preview, GPT-5 Chat and Qwen MT Plus 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.