Jamba Large vs o3-deep-research vs Qwen MT Plus
Jamba Large comes out ahead, 29 to 24 and 11 on our weighted score, and it is the cheaper option too.
- Our pick
AI21 Labs
Jamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
OpenAI
o3-deep-research
24/100- ECI—
- Price$9.00 / $36.00
- Context200K
Alibaba (Qwen)
Qwen MT Plus
11/100- ECI—
- Price$2.46 / $7.37
- Context16K
Jamba Large is our pick
Jamba Large is the better all-round choice, scoring 29/100 against o3-deep-research (24) and Qwen MT Plus (11). It leads on context window. o3-deep-research wins on inputs & features. 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 priceJamba LargeJamba Large $3.50 · Qwen MT Plus $3.69 · o3-deep-research $15.75 per 1M tokens (3:1 blend)
- Longest contextJamba LargeJamba Large 256,000 · o3-deep-research 200,000 · Qwen MT Plus 16,384 tokens
- Widest inputso3-deep-researchJamba Large: Text · o3-deep-research: Text, Images · Qwen MT Plus: Text
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | Jamba Large | o3-deep-research | Qwen MT Plus |
|---|---|---|---|---|
| Price | 50% | 23 | 0 | 22 |
| Inputs & features | 30% | 35 | 60 | 0 |
| Context window | 20% | 36 | 32 | 0 |
| Overall | 100% | 29/100 | 24/100 | 11/100 |
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 (best) | $9.00 | $2.46 |
| Output | $8.00 | $36.00 | $7.37 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $3.50 (best) | $15.75 | $3.69 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Median of 1 providers | Official Alibaba API |
| Limits | |||
| Context window | 256,000 tokens (best) | 200,000 tokens | 16,384 tokens |
| Max output | 4,096 tokens | 100,000 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | jamba-large | — | qwen-mt-plus |
| API providers | 1 | 1 | 3 (best) |
| Released | Jul 3, 2025 | Jun 26, 2025 | Jul 24, 2025 |
| Knowledge cutoff | Aug 22, 2024 | May 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
o3-deep-research$162.00
Qwen MT Plus$39.34
Which should you choose?
Which is better: Jamba Large, o3-deep-research or Qwen MT Plus?
Jamba Large is the better all-round choice, scoring 29/100 against o3-deep-research (24) and Qwen MT Plus (11). It leads on context window. o3-deep-research wins on inputs & features. 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, o3-deep-research or Qwen MT Plus?
Jamba Large is cheaper at $2.00 input / $8.00 output per million tokens (official AI21 Labs API price). Qwen MT Plus costs $2.46 input / $7.37 output per million tokens (official Alibaba API price); o3-deep-research costs $9.00 input / $36.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $3.50 per million tokens for Jamba Large versus $3.69 for Qwen MT Plus (1.1× as much) and $15.75 for o3-deep-research (4.5× 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, o3-deep-research has not been scored yet and Qwen MT Plus has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Jamba Large, o3-deep-research and Qwen MT Plus yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen MT Plus does not support tool calling, which most coding agents need.
Which has the bigger context window?
Jamba Large has the largest context window at 256,000 tokens, against 200,000 for o3-deep-research and 16,384 for Qwen MT Plus. Maximum output per response: Jamba Large up to 4,096, o3-deep-research up to 100,000, Qwen MT Plus up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Jamba Large accepts text; o3-deep-research accepts text and images; Qwen MT Plus accepts text. o3-deep-research handles the widest range of inputs.
Are any of these open source?
Jamba Large publishes its weights and can be self-hosted; o3-deep-research and Qwen MT Plus is proprietary.
Which is newer?
Qwen MT Plus is the newest, released Jul 24, 2025. Jamba Large came out Jul 3, 2025; o3-deep-research came out Jun 26, 2025. Knowledge cutoff: Jamba Large Aug 22, 2024, o3-deep-research May 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 Nov 2, 2026.