Gemini Robotics-ER 1.6 Preview vs Claude Sonnet 5.5
Too close to call on our weighted score (Claude Sonnet 5.5 46, Gemini Robotics-ER 1.6 Preview 46). The right pick depends on what you value most.
GoogleGemini Robotics-ER 1.6 Preview
46/100- ECI—
- Price$1.00 / $5.00
- Context131K
AnthropicClaude Sonnet 5.5
46/100- ECI166.7
- Price$2.00 / $10.00
- Context1M
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (Claude Sonnet 5.5 46/100, Gemini Robotics-ER 1.6 Preview 46/100), so choose by what matters most for your work: Gemini Robotics-ER 1.6 Preview on price and Claude Sonnet 5.5 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 priceGemini Robotics-ER 1.6 PreviewGemini Robotics-ER 1.6 Preview $2.00 · Claude Sonnet 5.5 $4.00 per 1M tokens (3:1 blend)
- Longest contextClaude Sonnet 5.5Claude Sonnet 5.5 1,000,000 · Gemini Robotics-ER 1.6 Preview 131,072 tokens
- Widest inputsGemini Robotics-ER 1.6 PreviewGemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video · Claude Sonnet 5.5: Text, Images, PDFs
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | Gemini Robotics-ER 1.6 Preview | Claude Sonnet 5.5 |
|---|---|---|---|
| Price | 50% | 34 | 20 |
| Inputs & features | 30% | 80 | 80 |
| Context window | 20% | 25 | 60 |
| Overall | 100% | 46/100 | 46/100 |
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 | Gemini Robotics-ER 1.6 PreviewGoogle | Claude Sonnet 5.5Anthropic |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 166.7 |
| ECI rank | — | #5 of 165 |
| GPQA DiamondGraduate-level science questions | — | 95.6% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 88.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 100% |
| SimpleQA VerifiedShort factual questions | — | 46.5% |
| Price per million tokens | ||
| Input | $1.00 (best) | $2.00 |
| Output | $5.00 (best) | $10.00 |
| Cached input | — | $0.10 |
| Blended (3:1) | $2.00 (best) | $4.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Anthropic API |
| Limits | ||
| Context window | 131,072 tokens | 1,000,000 tokens (best) |
| Max output | 65,536 tokens | 128,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | Yes |
| Audio | Yes | No |
| Video | Yes | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | — | claude-sonnet-5-5 |
| API providers | 1 | 34 (best) |
| Released | Apr 14, 2026 | Sep 28, 2026 |
| Knowledge cutoff | Jan 2025 | Jun 2026 |
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
- Claude Sonnet 5.5$40.00
Which should you choose?
Which is better: Gemini Robotics-ER 1.6 Preview or Claude Sonnet 5.5?
It is close. Our weighted score puts them within a point (Claude Sonnet 5.5 46/100, Gemini Robotics-ER 1.6 Preview 46/100), so choose by what matters most for your work: Gemini Robotics-ER 1.6 Preview on price and Claude Sonnet 5.5 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, Gemini Robotics-ER 1.6 Preview or Claude Sonnet 5.5?
Gemini Robotics-ER 1.6 Preview is cheaper at $1.00 input / $5.00 output per million tokens (median across 1 API provider). Claude Sonnet 5.5 costs $2.00 input / $10.00 output per million tokens (official Anthropic 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 $4.00 for Claude Sonnet 5.5 (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Gemini Robotics-ER 1.6 Preview has not been scored yet and Claude Sonnet 5.5 has an ECI of 166.7.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini Robotics-ER 1.6 Preview and Claude Sonnet 5.5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Claude Sonnet 5.5 has the largest context window at 1,000,000 tokens, against 131,072 for Gemini Robotics-ER 1.6 Preview. Maximum output per response: Gemini Robotics-ER 1.6 Preview up to 65,536, Claude Sonnet 5.5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video; Claude Sonnet 5.5 accepts text, images and PDFs. 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 and Claude Sonnet 5.5 are proprietary and only available through APIs and apps.
Which is newer?
Claude Sonnet 5.5 is the newest, released Sep 28, 2026. Gemini Robotics-ER 1.6 Preview came out Apr 14, 2026. Knowledge cutoff: Gemini Robotics-ER 1.6 Preview Jan 2025, Claude Sonnet 5.5 Jun 2026.
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.
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