Jamba Large vs DeepSeek V4 Pro
DeepSeek V4 Pro comes out ahead, 39 to 29 on our weighted score, and it is the cheaper option too.
AI21 Labs
Jamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
- Our pick
DeepSeek
DeepSeek V4 Pro
39/100- ECI—
- Price$1.60 / $3.30
- Context1M
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Make it a three-way comparison.
DeepSeek V4 Pro is our pick
DeepSeek V4 Pro is the better all-round choice, scoring 39/100 against Jamba Large (29). It leads on price and 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 priceDeepSeek V4 ProDeepSeek 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 tokens
- Widest inputsSame inputsJamba Large: Text · DeepSeek V4 Pro: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Jamba Large | DeepSeek V4 Pro |
|---|---|---|---|
| Price | 50% | 23 | 34 |
| Inputs & features | 30% | 35 | 35 |
| Context window | 20% | 36 | 60 |
| Overall | 100% | 29/100 | 39/100 |
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 | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $2.00 | $1.60 (best) |
| Output | $8.00 | $3.30 (best) |
| Cached input | — | — |
| Blended (3:1) | $3.50 | $2.03 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Median of 56 providers |
| Limits | ||
| Context window | 256,000 tokens | 1,000,000 tokens (best) |
| Max output | 4,096 tokens | 384,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | jamba-large | — |
| API providers | 1 | 58 (best) |
| Released | Jul 3, 2025 | Apr 24, 2026 |
| Knowledge cutoff | Aug 22, 2024 | May 2025 |
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
DeepSeek V4 Pro$22.60
Which should you choose?
Which is better: Jamba Large or DeepSeek V4 Pro?
DeepSeek V4 Pro is the better all-round choice, scoring 39/100 against Jamba Large (29). It leads on price and 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 or DeepSeek V4 Pro?
DeepSeek V4 Pro is cheaper at $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 $2.03 per million tokens for DeepSeek V4 Pro versus $3.50 for Jamba Large (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models 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 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. Both 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. Maximum output per response: Jamba Large up to 4,096, DeepSeek V4 Pro up to 384,000 tokens.
Which can read images, PDFs, audio or video?
Jamba Large accepts text; DeepSeek V4 Pro accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
DeepSeek V4 Pro is the newest, released Apr 24, 2026. Jamba Large came out Jul 3, 2025. Knowledge cutoff: 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.