o4-mini-deep-research vs Qwen3 Coder Plus vs Jamba Large
Too close to call on our weighted score (o4-mini-deep-research 37, Qwen3 Coder Plus 37, Jamba Large 29). The right pick depends on what you value most.
OpenAIo4-mini-deep-research
37/100- ECI—
- Price$1.80 / $7.20
- Context200K
Alibaba (Qwen)Qwen3 Coder Plus
37/100- ECI—
- Price$1.00 / $5.00
- Context1.05M
AI21 LabsJamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
Too close to call
It is close. Our weighted score puts them within a point (o4-mini-deep-research 37/100, Qwen3 Coder Plus 37/100, Jamba Large 29/100), so choose by what matters most for your work: Qwen3 Coder Plus on price and Qwen3 Coder Plus for long inputs. 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 priceQwen3 Coder PlusQwen3 Coder Plus $2.00 · o4-mini-deep-research $3.15 · Jamba Large $3.50 per 1M tokens (3:1 blend)
- Longest contextQwen3 Coder PlusQwen3 Coder Plus 1,048,576 · Jamba Large 256,000 · o4-mini-deep-research 200,000 tokens
- Widest inputso4-mini-deep-researcho4-mini-deep-research: Text, Images · Qwen3 Coder Plus: Text · Jamba Large: Text
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | o4-mini-deep-research | Qwen3 Coder Plus | Jamba Large |
|---|---|---|---|---|
| Price | 50% | 25 | 34 | 23 |
| Inputs & features | 30% | 60 | 25 | 35 |
| Context window | 20% | 32 | 61 | 36 |
| Overall | 100% | 37/100 | 37/100 | 29/100 |
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 | Qwen3 Coder PlusAlibaba (Qwen) | Jamba LargeAI21 Labs |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.80 | $1.00 (best) | $2.00 |
| Output | $7.20 | $5.00 (best) | $8.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.15 | $2.00 (best) | $3.50 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Alibaba API | Official AI21 Labs API |
| Limits | |||
| Context window | 200,000 tokens | 1,048,576 tokens (best) | 256,000 tokens |
| Max output | 100,000 tokens (best) | 65,536 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | — | qwen3-coder-plus | jamba-large |
| API providers | 1 | 5 (best) | 1 |
| Released | Jun 26, 2025 | Jul 23, 2025 | Jul 3, 2025 |
| Knowledge cutoff | May 2024 | Apr 2025 | 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.
- o4-mini-deep-research$32.40
- Qwen3 Coder Plus$20.00
- Jamba Large$36.00
Which should you choose?
Which is better: o4-mini-deep-research, Qwen3 Coder Plus or Jamba Large?
It is close. Our weighted score puts them within a point (o4-mini-deep-research 37/100, Qwen3 Coder Plus 37/100, Jamba Large 29/100), so choose by what matters most for your work: Qwen3 Coder Plus on price and Qwen3 Coder Plus for long inputs. 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, Qwen3 Coder Plus or Jamba Large?
Qwen3 Coder Plus is cheaper at $1.00 input / $5.00 output per million tokens (official Alibaba API price). o4-mini-deep-research costs $1.80 input / $7.20 output per million tokens (median across 1 API provider); 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 $2.00 per million tokens for Qwen3 Coder Plus versus $3.15 for o4-mini-deep-research (1.6× as much) and $3.50 for Jamba Large (1.8× 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, Qwen3 Coder Plus 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 o4-mini-deep-research, Qwen3 Coder Plus and Jamba Large 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?
Qwen3 Coder Plus 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, Qwen3 Coder Plus up to 65,536, Jamba Large up to 4,096 tokens.
Which can read images, PDFs, audio or video?
o4-mini-deep-research accepts text and images; Qwen3 Coder Plus accepts text; Jamba Large accepts text. o4-mini-deep-research 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 Qwen3 Coder Plus is proprietary.
Which is newer?
Qwen3 Coder Plus is the newest, released Jul 23, 2025. Jamba Large came out Jul 3, 2025; o4-mini-deep-research came out Jun 26, 2025. Knowledge cutoff: o4-mini-deep-research May 2024, Qwen3 Coder Plus Apr 2025, 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 Nov 2, 2026.
