o4-mini-deep-research vs Jamba Large vs Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 comes out ahead, 48 to 37 and 29 on our weighted score, though o4-mini-deep-research is 6% cheaper per token.
OpenAIo4-mini-deep-research
37/100- ECI—
- Price$1.80 / $7.20
- Context200K
AI21 LabsJamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
- Our pick
GoogleGemini 2.5 Pro Preview 06-05
48/100- ECI—
- Price$1.22 / $9.75
- Context1.05M
Gemini 2.5 Pro Preview 06-05 is our pick
Gemini 2.5 Pro Preview 06-05 is the better all-round choice, scoring 48/100 against o4-mini-deep-research (37) and Jamba Large (29). 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 priceo4-mini-deep-researcho4-mini-deep-research $3.15 · Gemini 2.5 Pro Preview 06-05 $3.35 · Jamba Large $3.50 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Pro Preview 06-05Gemini 2.5 Pro Preview 06-05 1,048,576 · Jamba Large 256,000 · o4-mini-deep-research 200,000 tokens
- Widest inputsGemini 2.5 Pro Preview 06-05o4-mini-deep-research: Text, Images · Jamba Large: Text · Gemini 2.5 Pro Preview 06-05: Text, Images, PDFs, Audio
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | o4-mini-deep-research | Jamba Large | Gemini 2.5 Pro Preview 06-05 |
|---|---|---|---|---|
| Price | 50% | 25 | 23 | 24 |
| Inputs & features | 30% | 60 | 35 | 80 |
| Context window | 20% | 32 | 36 | 61 |
| Overall | 100% | 37/100 | 29/100 | 48/100 |
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 | o4-mini-deep-researchOpenAI | Jamba LargeAI21 Labs | Gemini 2.5 Pro Preview 06-05Google |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.80 | $2.00 | $1.22 (best) |
| Output | $7.20 (best) | $8.00 | $9.75 |
| Cached input | — | — | — |
| Blended (3:1) | $3.15 (best) | $3.50 | $3.35 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official AI21 Labs API | Median of 4 providers |
| Limits | |||
| Context window | 200,000 tokens | 256,000 tokens | 1,048,576 tokens (best) |
| Max output | 100,000 tokens (best) | 4,096 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | — | jamba-large | — |
| API providers | 1 | 1 | 4 (best) |
| Released | Jun 26, 2025 | Jul 3, 2025 | Jun 5, 2025 |
| Knowledge cutoff | May 2024 | Aug 22, 2024 | Jan 31, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o4-mini-deep-research$32.40
- Jamba Large$36.00
- Gemini 2.5 Pro Preview 06-05$31.69
Which should you choose?
Which is better: o4-mini-deep-research, Jamba Large or Gemini 2.5 Pro Preview 06-05?
Gemini 2.5 Pro Preview 06-05 is the better all-round choice, scoring 48/100 against o4-mini-deep-research (37) and Jamba Large (29). 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, o4-mini-deep-research, Jamba Large or Gemini 2.5 Pro Preview 06-05?
o4-mini-deep-research is cheaper at $1.80 input / $7.20 output per million tokens (median across 1 API provider). Gemini 2.5 Pro Preview 06-05 costs $1.22 input / $9.75 output per million tokens (median across 4 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 $3.15 per million tokens for o4-mini-deep-research versus $3.35 for Gemini 2.5 Pro Preview 06-05 (1.1× as much) and $3.50 for Jamba Large (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. o4-mini-deep-research has not been scored yet, Jamba Large has not been scored yet and Gemini 2.5 Pro Preview 06-05 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for o4-mini-deep-research, Jamba Large and Gemini 2.5 Pro Preview 06-05 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?
Gemini 2.5 Pro Preview 06-05 has the largest context window at 1,048,576 tokens, against 256,000 for Jamba Large and 200,000 for o4-mini-deep-research. Maximum output per response: o4-mini-deep-research up to 100,000, Jamba Large up to 4,096, Gemini 2.5 Pro Preview 06-05 up to 65,536 tokens.
Which can read images, PDFs, audio or video?
o4-mini-deep-research accepts text and images; Jamba Large accepts text; Gemini 2.5 Pro Preview 06-05 accepts text, images, PDFs and audio. Gemini 2.5 Pro Preview 06-05 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 Gemini 2.5 Pro Preview 06-05 is proprietary.
Which is newer?
Jamba Large is the newest, released Jul 3, 2025. o4-mini-deep-research came out Jun 26, 2025; Gemini 2.5 Pro Preview 06-05 came out Jun 5, 2025. Knowledge cutoff: o4-mini-deep-research May 2024, Jamba Large Aug 22, 2024, Gemini 2.5 Pro Preview 06-05 Jan 31, 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.
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