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Comparison · 3 models · Updated Nov 2, 2026

Gemini Robotics-ER 1.6 Preview vs Jamba Large vs o4-mini-deep-research

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.

  1. Our pick

    Google

    Gemini Robotics-ER 1.6 Preview

    Released Apr 14, 2026

    46/100
    • ECI—
    • Price$1.00 / $5.00
    • Context131K
    Full specs Remove Gemini Robotics-ER 1.6 Preview

  2. AI21 Labs

    Jamba Large

    Released Jul 3, 2025

    29/100
    • ECI—
    • Price$2.00 / $8.00
    • Context256K
    Full specs Remove Jamba Large

  3. OpenAI

    o4-mini-deep-research

    Released Jun 26, 2025

    37/100
    • ECI—
    • Price$1.80 / $7.20
    • Context200K
    Full specs Remove o4-mini-deep-research
01 — Verdict

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 PreviewGemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video · Jamba Large: Text · o4-mini-deep-research: Text, Images
  • Self-hostingJamba LargePublishes downloadable weights
How the score is built
MeasureWeightGemini Robotics-ER 1.6 PreviewJamba Largeo4-mini-deep-research
Price50%342325
Inputs & features30%803560
Context window20%253632
Overall100%46/10029/10037/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Gemini Robotics-ER 1.6 Preview vs Jamba Large vs o4-mini-deep-research specifications side by side
SpecificationGemini Robotics-ER 1.6 PreviewGoogleJamba LargeAI21 Labso4-mini-deep-researchOpenAI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$1.00 (best)$2.00$1.80
Output$5.00 (best)$8.00$7.20
Cached input———
Blended (3:1)$2.00 (best)$3.50$3.15
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersOfficial AI21 Labs APIMedian of 1 providers
Limits
Context window131,072 tokens256,000 tokens (best)200,000 tokens
Max output65,536 tokens4,096 tokens100,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesNoYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsProprietaryOpenProprietary
API model ID—jamba-large—
API providers111
ReleasedApr 14, 2026Jul 3, 2025Jun 26, 2025
Knowledge cutoffJan 2025Aug 22, 2024May 2024
03 — Cost

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
  • Jamba Large$36.00
  • o4-mini-deep-research$32.40
04 — Questions

Which should you choose?

Which is better: Gemini Robotics-ER 1.6 Preview, Jamba Large or o4-mini-deep-research?

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, Gemini Robotics-ER 1.6 Preview, Jamba Large or o4-mini-deep-research?

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. Gemini Robotics-ER 1.6 Preview has not been scored yet, Jamba Large has not been scored yet and o4-mini-deep-research 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, Jamba Large and o4-mini-deep-research 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: Gemini Robotics-ER 1.6 Preview up to 65,536, Jamba Large up to 4,096, o4-mini-deep-research up to 100,000 tokens.

Which can read images, PDFs, audio or video?

Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video; Jamba Large accepts text; o4-mini-deep-research accepts text and images. 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; Gemini Robotics-ER 1.6 Preview and o4-mini-deep-research 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: Gemini Robotics-ER 1.6 Preview Jan 2025, Jamba Large Aug 22, 2024, o4-mini-deep-research May 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.

05 — Keep comparing

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