GPT-5.1 Codex vs Jamba Large
GPT-5.1 Codex comes out ahead, 42 to 30 on our weighted score, and it is the cheaper option too.
- Our pick
OpenAIGPT-5.1 Codex
42/100- ECI—
- Price$1.25 / $10.00
- Context400K
AI21 LabsJamba Large
30/100- ECI—
- Price$2.00 / $8.00
- Context256K
Add a model
Make it a three-way comparison.
GPT-5.1 Codex is our pick
GPT-5.1 Codex is the better all-round choice, scoring 42/100 against 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-5.1 CodexGPT-5.1 Codex $3.44 · Jamba Large $3.50 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 CodexGPT-5.1 Codex 400,000 · Jamba Large 256,000 tokens
- Widest inputsGPT-5.1 CodexGPT-5.1 Codex: Text, Images · Jamba Large: Text
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | GPT-5.1 Codex | Jamba Large |
|---|---|---|---|
| Price | 50% | 24 | 24 |
| Inputs & features | 30% | 70 | 35 |
| Context window | 20% | 44 | 36 |
| Overall | 100% | 42/100 | 30/100 |
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 | GPT-5.1 CodexOpenAI | Jamba LargeAI21 Labs |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $1.25 (best) | $2.00 |
| Output | $10.00 | $8.00 (best) |
| Cached input | — | — |
| Blended (3:1) | $3.44 (best) | $3.50 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 10 providers | Official AI21 Labs API |
| Limits | ||
| Context window | 400,000 tokens (best) | 256,000 tokens |
| Max output | 128,000 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | — | jamba-large |
| API providers | 10 (best) | 1 |
| Released | Nov 13, 2025 | Jul 1, 2025 |
| Knowledge cutoff | Sep 30, 2024 | Aug 22, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5.1 Codex$32.50
- Jamba Large$36.00
Which should you choose?
Which is better: GPT-5.1 Codex or Jamba Large?
GPT-5.1 Codex is the better all-round choice, scoring 42/100 against 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, GPT-5.1 Codex or Jamba Large?
GPT-5.1 Codex is cheaper at $1.25 input / $10.00 output per million tokens (median across 10 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 $3.44 per million tokens for GPT-5.1 Codex versus $3.50 for Jamba Large (1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GPT-5.1 Codex has not been scored yet and Jamba Large has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.1 Codex and Jamba Large 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?
GPT-5.1 Codex has the largest context window at 400,000 tokens, against 256,000 for Jamba Large. Maximum output per response: GPT-5.1 Codex up to 128,000, Jamba Large up to 4,096 tokens.
Which can read images, PDFs, audio or video?
GPT-5.1 Codex accepts text and images; Jamba Large accepts text. GPT-5.1 Codex handles the widest range of inputs.
Are any of these open source?
Jamba Large publishes its weights and can be self-hosted; GPT-5.1 Codex is proprietary.
Which is newer?
GPT-5.1 Codex is the newest, released Nov 13, 2025. Jamba Large came out Jul 1, 2025. Knowledge cutoff: GPT-5.1 Codex Sep 30, 2024, Jamba Large Aug 22, 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.
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