GPT-5.1 Codex Max vs Jamba Large vs Gemini 2.5 Computer Use Preview
GPT-5.1 Codex Max comes out ahead, 42 to 35 and 30 on our weighted score.
- Our pick
OpenAIGPT-5.1 Codex Max
42/100- ECI—
- Price$1.25 / $10.00
- Context400K
AI21 LabsJamba Large
30/100- ECI—
- Price$2.00 / $8.00
- Context256K
GoogleGemini 2.5 Computer Use Preview
35/100- ECI—
- Price$1.25 / $10.00
- Context128K
GPT-5.1 Codex Max is our pick
GPT-5.1 Codex Max is the better all-round choice, scoring 42/100 against Gemini 2.5 Computer Use Preview (35) 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-5.1 Codex Max and Gemini 2.5 Computer Use PreviewGPT-5.1 Codex Max $3.44 · Gemini 2.5 Computer Use Preview $3.44 · Jamba Large $3.50 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex MaxGPT-5.1 Codex Max 400,000 · Jamba Large 256,000 · Gemini 2.5 Computer Use Preview 128,000 tokens
- Widest inputsGPT-5.1 Codex Max and Gemini 2.5 Computer Use PreviewGPT-5.1 Codex Max: Text, Images · Jamba Large: Text · Gemini 2.5 Computer Use Preview: Text, Images
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | GPT-5.1 Codex Max | Jamba Large | Gemini 2.5 Computer Use Preview |
|---|---|---|---|---|
| Price | 50% | 24 | 24 | 24 |
| Inputs & features | 30% | 70 | 35 | 60 |
| Context window | 20% | 44 | 36 | 24 |
| Overall | 100% | 42/100 | 30/100 | 35/100 |
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 Codex MaxOpenAI | Jamba LargeAI21 Labs | Gemini 2.5 Computer Use PreviewGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.25 (best) | $2.00 | $1.25 (best) |
| Output | $10.00 | $8.00 (best) | $10.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.44 (best) | $3.50 | $3.44 (best) |
| Long-context rate | Same rate | Same rate | Over 200K: $2.50 / $15.00 |
| Price source | Median of 8 providers | Official AI21 Labs API | Official Google API |
| Limits | |||
| Context window | 400,000 tokens (best) | 256,000 tokens | 128,000 tokens |
| Max output | 128,000 tokens (best) | 4,096 tokens | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | — | jamba-large | gemini-2.5-computer-use-preview-10-2025 |
| API providers | 8 (best) | 1 | 2 |
| Released | Nov 13, 2025 | Jul 1, 2025 | Oct 7, 2025 |
| Knowledge cutoff | Sep 30, 2024 | Aug 22, 2024 | Jan 2025 |
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 Max$32.50
- Jamba Large$36.00
- Gemini 2.5 Computer Use Preview$32.50
Which should you choose?
Which is better: GPT-5.1 Codex Max, Jamba Large or Gemini 2.5 Computer Use Preview?
GPT-5.1 Codex Max is the better all-round choice, scoring 42/100 against Gemini 2.5 Computer Use Preview (35) 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, GPT-5.1 Codex Max, Jamba Large or Gemini 2.5 Computer Use Preview?
GPT-5.1 Codex Max is cheaper at $1.25 input / $10.00 output per million tokens (median across 8 API providers). Gemini 2.5 Computer Use Preview costs $1.25 input / $10.00 output per million tokens (official Google API price); 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 Max versus $3.44 for Gemini 2.5 Computer Use Preview (1× as much) and $3.50 for Jamba Large (1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.1 Codex Max has not been scored yet, Jamba Large has not been scored yet and Gemini 2.5 Computer Use Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.1 Codex Max, Jamba Large and Gemini 2.5 Computer Use Preview 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?
GPT-5.1 Codex Max has the largest context window at 400,000 tokens, against 256,000 for Jamba Large and 128,000 for Gemini 2.5 Computer Use Preview. Maximum output per response: GPT-5.1 Codex Max up to 128,000, Jamba Large up to 4,096, Gemini 2.5 Computer Use Preview up to 64,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.1 Codex Max accepts text and images; Jamba Large accepts text; Gemini 2.5 Computer Use Preview accepts text and images. GPT-5.1 Codex Max 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 Max and Gemini 2.5 Computer Use Preview is proprietary.
Which is newer?
GPT-5.1 Codex Max is the newest, released Nov 13, 2025. Gemini 2.5 Computer Use Preview came out Oct 7, 2025; Jamba Large came out Jul 1, 2025. Knowledge cutoff: GPT-5.1 Codex Max Sep 30, 2024, Jamba Large Aug 22, 2024, Gemini 2.5 Computer Use Preview Jan 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 Oct 4, 2026.
