Jamba Large vs o4-mini-deep-research vs Palmyra X4
o4-mini-deep-research comes out ahead, 37 to 29 and 25 on our weighted score, and it is the cheaper option too.
AI21 LabsJamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
- Our pick
OpenAIo4-mini-deep-research
37/100- ECI—
- Price$1.80 / $7.20
- Context200K
Writer
Palmyra X4
25/100- ECI—
- Price$2.50 / $10.00
- Context128K
o4-mini-deep-research is our pick
o4-mini-deep-research is the better all-round choice, scoring 37/100 against Jamba Large (29) and Palmyra X4 (25). 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 · Palmyra X4 $4.38 per 1M tokens (3:1 blend)
- Longest contextJamba LargeJamba Large 256,000 · o4-mini-deep-research 200,000 · Palmyra X4 128,000 tokens
- Widest inputso4-mini-deep-researchJamba Large: Text · o4-mini-deep-research: Text, Images · Palmyra X4: Text
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | Jamba Large | o4-mini-deep-research | Palmyra X4 |
|---|---|---|---|---|
| Price | 50% | 23 | 25 | 19 |
| Inputs & features | 30% | 35 | 60 | 35 |
| Context window | 20% | 36 | 32 | 24 |
| Overall | 100% | 29/100 | 37/100 | 25/100 |
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 | Jamba LargeAI21 Labs | o4-mini-deep-researchOpenAI | Palmyra X4Writer |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.00 | $1.80 (best) | $2.50 |
| Output | $8.00 | $7.20 (best) | $10.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.50 | $3.15 (best) | $4.38 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Median of 1 providers | Median of 2 providers |
| Limits | |||
| Context window | 256,000 tokens (best) | 200,000 tokens | 128,000 tokens |
| Max output | 4,096 tokens | 100,000 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | jamba-large | — | — |
| API providers | 1 | 1 | 2 (best) |
| Released | Jul 3, 2025 | Jun 26, 2025 | Oct 9, 2024 |
| 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
- o4-mini-deep-research$32.40
- Palmyra X4$45.00
Which should you choose?
Which is better: Jamba Large, o4-mini-deep-research or Palmyra X4?
o4-mini-deep-research is the better all-round choice, scoring 37/100 against Jamba Large (29) and Palmyra X4 (25). 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, Jamba Large, o4-mini-deep-research or Palmyra X4?
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); Palmyra X4 costs $2.50 input / $10.00 output per million tokens (median across 2 API providers). 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) and $4.38 for Palmyra X4 (1.4× 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, o4-mini-deep-research has not been scored yet and Palmyra X4 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Jamba Large, o4-mini-deep-research and Palmyra X4 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 128,000 for Palmyra X4. Maximum output per response: Jamba Large up to 4,096, o4-mini-deep-research up to 100,000, Palmyra X4 up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Jamba Large accepts text; o4-mini-deep-research accepts text and images; Palmyra X4 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 and Palmyra X4 is proprietary.
Which is newer?
Jamba Large is the newest, released Jul 3, 2025. o4-mini-deep-research came out Jun 26, 2025; Palmyra X4 came out Oct 9, 2024. 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.
