GLM-5-Turbo vs Kimi K2.6 vs Gemini Robotics-ER 1.6 Preview
Too close to call on our weighted score (Kimi K2.6 51, Gemini Robotics-ER 1.6 Preview 50, GLM-5-Turbo 38). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-5-Turbo
38/100- ECI—
- Price$1.20 / $4.00
- Context200K
Moonshot AIKimi K2.6
51/100- ECI151.1
- Price$0.95 / $4.00
- Context262K
GoogleGemini Robotics-ER 1.6 Preview
50/100- ECI—
- Price$1.00 / $5.00
- Context131K
Too close to call
It is close. Our weighted score puts them within 1 points (Kimi K2.6 51/100, Gemini Robotics-ER 1.6 Preview 50/100, GLM-5-Turbo 38/100), so choose by what matters most for your work: Kimi K2.6 on price and Kimi K2.6 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 priceKimi K2.6Kimi K2.6 $1.71 · GLM-5-Turbo $1.90 · Gemini Robotics-ER 1.6 Preview $2.00 per 1M tokens (3:1 blend)
- Longest contextKimi K2.6Kimi K2.6 262,144 · GLM-5-Turbo 200,000 · Gemini Robotics-ER 1.6 Preview 131,072 tokens
- Widest inputsGemini Robotics-ER 1.6 PreviewGLM-5-Turbo: Text · Kimi K2.6: Text, Images, Video · Gemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video
- Self-hostingKimi K2.6Publishes downloadable weights
| Measure | Weight | GLM-5-Turbo | Kimi K2.6 | Gemini Robotics-ER 1.6 Preview |
|---|---|---|---|---|
| Price | 50% | 37 | 39 | 36 |
| Inputs & features | 30% | 45 | 80 | 90 |
| Context window | 20% | 32 | 37 | 24 |
| Overall | 100% | 38/100 | 51/100 | 50/100 |
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 | GLM-5-TurboZ.ai (Zhipu) | Kimi K2.6Moonshot AI | Gemini Robotics-ER 1.6 PreviewGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 151.1 | — |
| ECI rank | — | #45 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 90.8% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 57.2% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 96.1% | — |
| SWE-bench VerifiedFixing real GitHub issues | — | 76.7% | — |
| SimpleQA VerifiedShort factual questions | — | 34.9% | — |
| Price per million tokens | |||
| Input | $1.20 | $0.95 (best) | $1.00 |
| Output | $4.00 (best) | $4.00 (best) | $5.00 |
| Cached input | $0.24 | $0.16 (best) | — |
| Blended (3:1) | $1.90 | $1.71 (best) | $2.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Moonshot AI API | Median of 1 providers |
| Limits | |||
| Context window | 200,000 tokens | 262,144 tokens (best) | 131,072 tokens |
| Max output | 131,072 tokens | 262,144 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | Yes | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | glm-5-turbo | kimi-k2.6 | — |
| API providers | 17 | 46 (best) | 1 |
| Released | Mar 16, 2026 | Apr 21, 2026 | Apr 14, 2026 |
| Knowledge cutoff | — | Jan 2025 | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5-Turbo$20.00
- Kimi K2.6$17.50
- Gemini Robotics-ER 1.6 Preview$20.00
Which should you choose?
Which is better: GLM-5-Turbo, Kimi K2.6 or Gemini Robotics-ER 1.6 Preview?
It is close. Our weighted score puts them within 1 points (Kimi K2.6 51/100, Gemini Robotics-ER 1.6 Preview 50/100, GLM-5-Turbo 38/100), so choose by what matters most for your work: Kimi K2.6 on price and Kimi K2.6 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, GLM-5-Turbo, Kimi K2.6 or Gemini Robotics-ER 1.6 Preview?
Kimi K2.6 is cheaper at $0.95 input / $4.00 output per million tokens (official Moonshot AI API price). GLM-5-Turbo costs $1.20 input / $4.00 output per million tokens (official Z.AI API price); Gemini Robotics-ER 1.6 Preview costs $1.00 input / $5.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $1.71 per million tokens for Kimi K2.6 versus $1.90 for GLM-5-Turbo (1.1× as much) and $2.00 for Gemini Robotics-ER 1.6 Preview (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-5-Turbo has not been scored yet, Kimi K2.6 has an ECI of 151.1 and Gemini Robotics-ER 1.6 Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5-Turbo and Gemini Robotics-ER 1.6 Preview 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?
Kimi K2.6 has the largest context window at 262,144 tokens, against 200,000 for GLM-5-Turbo and 131,072 for Gemini Robotics-ER 1.6 Preview. Maximum output per response: GLM-5-Turbo up to 131,072, Kimi K2.6 up to 262,144, Gemini Robotics-ER 1.6 Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-5-Turbo accepts text; Kimi K2.6 accepts text, images and video; Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video. Gemini Robotics-ER 1.6 Preview handles the widest range of inputs.
Are any of these open source?
Kimi K2.6 publishes its weights and can be self-hosted; GLM-5-Turbo and Gemini Robotics-ER 1.6 Preview is proprietary.
Which is newer?
Kimi K2.6 is the newest, released Apr 21, 2026. Gemini Robotics-ER 1.6 Preview came out Apr 14, 2026; GLM-5-Turbo came out Mar 16, 2026. Knowledge cutoff: Kimi K2.6 Jan 2025, Gemini Robotics-ER 1.6 Preview Jan 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.
