o4-mini-deep-research vs Gemini Robotics-ER 1.6 Preview vs Jamba Large
Gemini Robotics-ER 1.6 Preview comes out ahead, 46 to 37 and 29 on our weighted score, and it is the cheaper option too.
OpenAIo4-mini-deep-research
37/100- ECI—
- Price$1.80 / $7.20
- Context200K
- Our pick
GoogleGemini Robotics-ER 1.6 Preview
46/100- ECI—
- Price$1.00 / $5.00
- Context131K
AI21 LabsJamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
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 o4-mini-deep-research (37) and Jamba Large (29). It leads on price and inputs & features. Jamba Large 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 · o4-mini-deep-research $3.15 · Jamba Large $3.50 per 1M tokens (3:1 blend)
- Longest contextJamba LargeJamba Large 256,000 · o4-mini-deep-research 200,000 · Gemini Robotics-ER 1.6 Preview 131,072 tokens
- Widest inputsGemini Robotics-ER 1.6 Previewo4-mini-deep-research: Text, Images · Gemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video · Jamba Large: Text
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | o4-mini-deep-research | Gemini Robotics-ER 1.6 Preview | Jamba Large |
|---|---|---|---|---|
| Price | 50% | 25 | 34 | 23 |
| Inputs & features | 30% | 60 | 80 | 35 |
| Context window | 20% | 32 | 25 | 36 |
| Overall | 100% | 37/100 | 46/100 | 29/100 |
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 | o4-mini-deep-researchOpenAI | Gemini Robotics-ER 1.6 PreviewGoogle | Jamba LargeAI21 Labs |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.80 | $1.00 (best) | $2.00 |
| Output | $7.20 | $5.00 (best) | $8.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.15 | $2.00 (best) | $3.50 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 1 providers | Official AI21 Labs API |
| Limits | |||
| Context window | 200,000 tokens | 131,072 tokens | 256,000 tokens (best) |
| Max output | 100,000 tokens (best) | 65,536 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | — | — | jamba-large |
| API providers | 1 | 1 | 1 |
| Released | Jun 26, 2025 | Apr 14, 2026 | Jul 3, 2025 |
| Knowledge cutoff | May 2024 | Jan 2025 | Aug 22, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o4-mini-deep-research$32.40
- Gemini Robotics-ER 1.6 Preview$20.00
- Jamba Large$36.00
Which should you choose?
Which is better: o4-mini-deep-research, Gemini Robotics-ER 1.6 Preview or Jamba Large?
Gemini Robotics-ER 1.6 Preview is the better all-round choice, scoring 46/100 against o4-mini-deep-research (37) and Jamba Large (29). It leads on price and inputs & features. Jamba Large 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, o4-mini-deep-research, Gemini Robotics-ER 1.6 Preview or Jamba Large?
Gemini Robotics-ER 1.6 Preview is cheaper at $1.00 input / $5.00 output per million tokens (median across 1 API provider). o4-mini-deep-research costs $1.80 input / $7.20 output per million tokens (median across 1 API provider); Jamba Large costs $2.00 input / $8.00 output per million tokens (official AI21 Labs 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 $3.15 for o4-mini-deep-research (1.6× as much) and $3.50 for Jamba Large (1.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. o4-mini-deep-research has not been scored yet, Gemini Robotics-ER 1.6 Preview has not been scored yet and Jamba Large has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for o4-mini-deep-research, Gemini Robotics-ER 1.6 Preview and Jamba Large 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?
Jamba Large has the largest context window at 256,000 tokens, against 200,000 for o4-mini-deep-research and 131,072 for Gemini Robotics-ER 1.6 Preview. Maximum output per response: o4-mini-deep-research up to 100,000, Gemini Robotics-ER 1.6 Preview up to 65,536, Jamba Large up to 4,096 tokens.
Which can read images, PDFs, audio or video?
o4-mini-deep-research accepts text and images; Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video; Jamba Large accepts text. Gemini Robotics-ER 1.6 Preview handles the widest range of inputs.
Are any of these open source?
Jamba Large publishes its weights and can be self-hosted; o4-mini-deep-research and Gemini Robotics-ER 1.6 Preview is proprietary.
Which is newer?
Gemini Robotics-ER 1.6 Preview is the newest, released Apr 14, 2026. Jamba Large came out Jul 3, 2025; o4-mini-deep-research came out Jun 26, 2025. Knowledge cutoff: o4-mini-deep-research May 2024, Gemini Robotics-ER 1.6 Preview Jan 2025, Jamba Large Aug 22, 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.
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