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Comparison · 2 models · Updated Nov 2, 2026

o4-mini-deep-research vs Jamba Large

o4-mini-deep-research comes out ahead, 37 to 29 on our weighted score, and it is the cheaper option too.

  1. Our pick

    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

  2. AI21 Labs

    Jamba Large

    Released Jul 3, 2025

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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

o4-mini-deep-research is our pick

o4-mini-deep-research is the better all-round choice, scoring 37/100 against 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 priceo4-mini-deep-researcho4-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 tokens
  • Widest inputso4-mini-deep-researcho4-mini-deep-research: Text, Images · Jamba Large: Text
  • Self-hostingJamba LargePublishes downloadable weights
How the score is built
MeasureWeighto4-mini-deep-researchJamba Large
Price50%2523
Inputs & features30%6035
Context window20%3236
Overall100%37/10029/100

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.

o4-mini-deep-research vs Jamba Large specifications side by side
Specificationo4-mini-deep-researchOpenAIJamba LargeAI21 Labs
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$1.80 (best)$2.00
Output$7.20 (best)$8.00
Cached input——
Blended (3:1)$3.15 (best)$3.50
Long-context rateSame rateSame rate
Price sourceMedian of 1 providersOfficial AI21 Labs API
Limits
Context window200,000 tokens256,000 tokens (best)
Max output100,000 tokens (best)4,096 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesNo
Tool callingYesYes
Structured outputNoYes
Availability
WeightsProprietaryOpen
API model ID—jamba-large
API providers11
ReleasedJun 26, 2025Jul 3, 2025
Knowledge cutoffMay 2024Aug 22, 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.

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

Which should you choose?

Which is better: o4-mini-deep-research or Jamba Large?

o4-mini-deep-research is the better all-round choice, scoring 37/100 against 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 or Jamba Large?

o4-mini-deep-research is cheaper at $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 $3.15 per million tokens for o4-mini-deep-research versus $3.50 for Jamba Large (1.1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. o4-mini-deep-research 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 and Jamba Large 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?

Jamba Large has the largest context window at 256,000 tokens, against 200,000 for o4-mini-deep-research. Maximum output per response: o4-mini-deep-research up to 100,000, Jamba Large up to 4,096 tokens.

Which can read images, PDFs, audio or video?

o4-mini-deep-research accepts text and images; Jamba Large accepts text. o4-mini-deep-research 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 is proprietary.

Which is newer?

Jamba Large is the newest, released Jul 3, 2025. o4-mini-deep-research came out Jun 26, 2025. Knowledge cutoff: o4-mini-deep-research May 2024, 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.

05 — Keep comparing

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