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Comparison · 3 models · Updated Nov 2, 2026

Gemini Robotics-ER 1.6 Preview vs Jamba Large vs DeepSeek V4 Pro

Gemini Robotics-ER 1.6 Preview comes out ahead, 46 to 39 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
  2. AI21 Labs

    Jamba Large

    Released Jul 3, 2025

    29/100
    • ECI—
    • Price$2.00 / $8.00
    • Context256K
  3. DeepSeek

    DeepSeek V4 Pro

    Released Apr 24, 2026

    39/100
    • ECI—
    • Price$1.60 / $3.30
    • Context1M
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 DeepSeek V4 Pro (39) and Jamba Large (29). It leads on inputs & features. DeepSeek V4 Pro 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 · DeepSeek V4 Pro $2.03 · Jamba Large $3.50 per 1M tokens (3:1 blend)
  • Longest contextDeepSeek V4 ProDeepSeek V4 Pro 1,000,000 · Jamba Large 256,000 · 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 · DeepSeek V4 Pro: Text
  • Self-hostingJamba Large and DeepSeek V4 ProPublishes downloadable weights
How the score is built
MeasureWeightGemini Robotics-ER 1.6 PreviewJamba LargeDeepSeek V4 Pro
Price50%342334
Inputs & features30%803535
Context window20%253660
Overall100%46/10029/10039/100

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 DeepSeek V4 Pro specifications side by side
SpecificationGemini Robotics-ER 1.6 PreviewGoogleJamba LargeAI21 LabsDeepSeek V4 ProDeepSeek
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$1.00 (best)$2.00$1.60
Output$5.00$8.00$3.30 (best)
Cached input———
Blended (3:1)$2.00 (best)$3.50$2.03
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersOfficial AI21 Labs APIMedian of 56 providers
Limits
Context window131,072 tokens256,000 tokens1,000,000 tokens (best)
Max output65,536 tokens4,096 tokens384,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsNoNoNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesNoYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsProprietaryOpenOpen
API model ID—jamba-large—
API providers1158 (best)
ReleasedApr 14, 2026Jul 3, 2025Apr 24, 2026
Knowledge cutoffJan 2025Aug 22, 2024May 2025
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
  • DeepSeek V4 Pro$22.60
04 — Questions

Which should you choose?

Which is better: Gemini Robotics-ER 1.6 Preview, Jamba Large or DeepSeek V4 Pro?

Gemini Robotics-ER 1.6 Preview is the better all-round choice, scoring 46/100 against DeepSeek V4 Pro (39) and Jamba Large (29). It leads on inputs & features. DeepSeek V4 Pro 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 DeepSeek V4 Pro?

Gemini Robotics-ER 1.6 Preview is cheaper at $1.00 input / $5.00 output per million tokens (median across 1 API provider). DeepSeek V4 Pro costs $1.60 input / $3.30 output per million tokens (median across 56 API providers); 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 $2.03 for DeepSeek V4 Pro (1× 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 DeepSeek V4 Pro 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 DeepSeek V4 Pro 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?

DeepSeek V4 Pro has the largest context window at 1,000,000 tokens, against 256,000 for Jamba Large 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, DeepSeek V4 Pro up to 384,000 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; DeepSeek V4 Pro accepts text. Gemini Robotics-ER 1.6 Preview handles the widest range of inputs.

Are any of these open source?

Jamba Large and DeepSeek V4 Pro publishes its weights and can be self-hosted; Gemini Robotics-ER 1.6 Preview is proprietary.

Which is newer?

DeepSeek V4 Pro is the newest, released Apr 24, 2026. Gemini Robotics-ER 1.6 Preview came out Apr 14, 2026; Jamba Large came out Jul 3, 2025. Knowledge cutoff: Gemini Robotics-ER 1.6 Preview Jan 2025, Jamba Large Aug 22, 2024, DeepSeek V4 Pro May 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 Nov 2, 2026.