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.
AI21 Labs
Jamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
Morph
Morph V3 Fast
32/100- ECI—
- Price$0.80 / $1.20
- Context262K
- Our pick
OpenAI
o4-mini-deep-research
37/100- ECI—
- Price$1.80 / $7.20
- Context200K
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
| Measure | Weight | Jamba Large | Morph V3 Fast | o4-mini-deep-research |
|---|---|---|---|---|
| Price | 50% | 23 | 50 | 25 |
| Inputs & features | 30% | 35 | 0 | 60 |
| Context window | 20% | 36 | 37 | 32 |
| Overall | 100% | 29/100 | 32/100 | 37/100 |
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 | Morph V3 FastMorph | ||
|---|---|---|---|
| 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 rate | Same rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Median of 5 providers | Median of 1 providers |
| Limits | |||
| Context window | 256,000 tokens | 262,144 tokens (best) | 200,000 tokens |
| Max output | 4,096 tokens | 131,072 tokens (best) | 100,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | Yes | No | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | jamba-large | — | — |
| API providers | 1 | 5 (best) | 1 |
| Released | Jul 3, 2025 | Jul 7, 2025 | Jun 26, 2025 |
| Knowledge cutoff | Aug 22, 2024 | — | May 2024 |
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
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.