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Comparison · 3 models · Updated Nov 2, 2026

Jamba Large vs Morph V3 Fast vs o4-mini-deep-research

o4-mini-deep-research comes out ahead, 37 to 32 and 29 on our weighted score, though Morph V3 Fast is 3.5× cheaper per token.

  1. AI21 Labs

    Jamba Large

    Released Jul 3, 2025

    29/100
    • ECI—
    • Price$2.00 / $8.00
    • Context256K
  2. Morph

    Morph V3 Fast

    Released Jul 7, 2025

    32/100
    • ECI—
    • Price$0.80 / $1.20
    • Context262K
  3. Our pick

    OpenAI

    o4-mini-deep-research

    Released Jun 26, 2025

    37/100
    • ECI—
    • Price$1.80 / $7.20
    • Context200K
01 — Verdict

o4-mini-deep-research is our pick

o4-mini-deep-research is the better all-round choice, scoring 37/100 against Morph V3 Fast (32) and Jamba Large (29). It leads on inputs & features. Morph V3 Fast wins on price. 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 priceMorph V3 FastMorph V3 Fast $0.90 · o4-mini-deep-research $3.15 · Jamba Large $3.50 per 1M tokens (3:1 blend)
  • Longest contextMorph V3 FastMorph V3 Fast 262,144 · Jamba Large 256,000 · o4-mini-deep-research 200,000 tokens
  • Widest inputso4-mini-deep-researchJamba Large: Text · Morph V3 Fast: Text · o4-mini-deep-research: Text, Images
  • Self-hostingJamba LargePublishes downloadable weights
How the score is built
MeasureWeightJamba LargeMorph V3 Fasto4-mini-deep-research
Price50%235025
Inputs & features30%35060
Context window20%363732
Overall100%29/10032/10037/100

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.

Jamba Large vs Morph V3 Fast vs o4-mini-deep-research specifications side by side
SpecificationJamba LargeAI21 LabsMorph V3 FastMorpho4-mini-deep-researchOpenAI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$2.00$0.80 (best)$1.80
Output$8.00$1.20 (best)$7.20
Cached input———
Blended (3:1)$3.50$0.90 (best)$3.15
Long-context rateSame rateSame rateSame rate
Price sourceOfficial AI21 Labs APIMedian of 5 providersMedian of 1 providers
Limits
Context window256,000 tokens262,144 tokens (best)200,000 tokens
Max output4,096 tokens131,072 tokens (best)100,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoYes
Tool callingYesNoYes
Structured outputYesNoNo
Availability
WeightsOpenProprietaryProprietary
API model IDjamba-large——
API providers15 (best)1
ReleasedJul 3, 2025Jul 7, 2025Jun 26, 2025
Knowledge cutoffAug 22, 2024—May 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.

  • Jamba Large$36.00
  • Morph V3 Fast$10.40
  • o4-mini-deep-research$32.40
04 — Questions

Which should you choose?

Which is better: Jamba Large, Morph V3 Fast or o4-mini-deep-research?

o4-mini-deep-research is the better all-round choice, scoring 37/100 against Morph V3 Fast (32) and Jamba Large (29). It leads on inputs & features. Morph V3 Fast wins on price. 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, Jamba Large, Morph V3 Fast or o4-mini-deep-research?

Morph V3 Fast is cheaper at $0.80 input / $1.20 output per million tokens (median across 5 API providers). 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 $0.90 per million tokens for Morph V3 Fast versus $3.15 for o4-mini-deep-research (3.5× as much) and $3.50 for Jamba Large (3.9× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Jamba Large has not been scored yet, Morph V3 Fast 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 Jamba Large, Morph V3 Fast and o4-mini-deep-research yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Morph V3 Fast does not support tool calling, which most coding agents need.

Which has the bigger context window?

Morph V3 Fast has the largest context window at 262,144 tokens, against 256,000 for Jamba Large and 200,000 for o4-mini-deep-research. Maximum output per response: Jamba Large up to 4,096, Morph V3 Fast up to 131,072, o4-mini-deep-research up to 100,000 tokens.

Which can read images, PDFs, audio or video?

Jamba Large accepts text; Morph V3 Fast accepts text; o4-mini-deep-research accepts text and images. 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; Morph V3 Fast and o4-mini-deep-research is proprietary.

Which is newer?

Morph V3 Fast is the newest, released Jul 7, 2025. Jamba Large came out Jul 3, 2025; o4-mini-deep-research came out Jun 26, 2025. Knowledge cutoff: 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.