Jamba Large vs Nova Premier vs GPT-5 Chat
Nova Premier comes out ahead, 41 to 34 and 30 on our weighted score, though GPT-5 Chat is 31% cheaper per token.
AI21 LabsJamba Large
30/100- ECI—
- Price$2.00 / $8.00
- Context256K
- Our pick
AmazonNova Premier
41/100- ECI—
- Price$2.50 / $12.50
- Context1M
OpenAIGPT-5 Chat
34/100- ECI—
- Price$1.25 / $10.00
- Context400K
Nova Premier is our pick
Nova Premier is the better all-round choice, scoring 41/100 against GPT-5 Chat (34) and Jamba Large (30). It leads on inputs & features 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 priceGPT-5 ChatGPT-5 Chat $3.44 · Jamba Large $3.50 · Nova Premier $5.00 per 1M tokens (3:1 blend)
- Longest contextNova PremierNova Premier 1,000,000 · GPT-5 Chat 400,000 · Jamba Large 256,000 tokens
- Widest inputsNova PremierJamba Large: Text · Nova Premier: Text, Images, PDFs, Video · GPT-5 Chat: Text, Images
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | Jamba Large | Nova Premier | GPT-5 Chat |
|---|---|---|---|---|
| Price | 50% | 24 | 17 | 24 |
| Inputs & features | 30% | 35 | 70 | 45 |
| Context window | 20% | 36 | 60 | 44 |
| Overall | 100% | 30/100 | 41/100 | 34/100 |
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 | Nova PremierAmazon | GPT-5 ChatOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.00 | $2.50 | $1.25 (best) |
| Output | $8.00 (best) | $12.50 | $10.00 |
| Cached input | — | $0.625 | — |
| Blended (3:1) | $3.50 | $5.00 | $3.44 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Official Amazon Bedrock API | Median of 2 providers |
| Limits | |||
| Context window | 256,000 tokens | 1,000,000 tokens (best) | 400,000 tokens |
| Max output | 4,096 tokens | 10,000 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | No | No | Yes |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | jamba-large | us.amazon.nova-premier-v1:0 | — |
| API providers | 1 | 1 | 2 (best) |
| Released | Jul 1, 2025 | Apr 30, 2025 | Aug 7, 2025 |
| Knowledge cutoff | Aug 22, 2024 | Oct 2024 | Sep 30, 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
- Nova Premier$50.00
- GPT-5 Chat$32.50
Which should you choose?
Which is better: Jamba Large, Nova Premier or GPT-5 Chat?
Nova Premier is the better all-round choice, scoring 41/100 against GPT-5 Chat (34) and Jamba Large (30). It leads on inputs & features 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, Nova Premier or GPT-5 Chat?
GPT-5 Chat is cheaper at $1.25 input / $10.00 output per million tokens (median across 2 API providers). Jamba Large costs $2.00 input / $8.00 output per million tokens (official AI21 Labs API price); Nova Premier costs $2.50 input / $12.50 output per million tokens (official Amazon Bedrock API price). At a typical mix of three input tokens to one output token, that is $3.44 per million tokens for GPT-5 Chat versus $3.50 for Jamba Large (1× as much) and $5.00 for Nova Premier (1.5× 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, Nova Premier has not been scored yet and GPT-5 Chat has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Jamba Large, Nova Premier and GPT-5 Chat yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that GPT-5 Chat does not support tool calling, which most coding agents need.
Which has the bigger context window?
Nova Premier has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5 Chat and 256,000 for Jamba Large. Maximum output per response: Jamba Large up to 4,096, Nova Premier up to 10,000, GPT-5 Chat up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Jamba Large accepts text; Nova Premier accepts text, images, PDFs and video; GPT-5 Chat accepts text and images. Nova Premier handles the widest range of inputs.
Are any of these open source?
Jamba Large publishes its weights and can be self-hosted; Nova Premier and GPT-5 Chat is proprietary.
Which is newer?
GPT-5 Chat is the newest, released Aug 7, 2025. Jamba Large came out Jul 1, 2025; Nova Premier came out Apr 30, 2025. Knowledge cutoff: Jamba Large Aug 22, 2024, Nova Premier Oct 2024, GPT-5 Chat Sep 30, 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 Oct 4, 2026.
