Jamba Mini vs Llama-3.2-11B-Vision-Instruct vs Qwen-MT Turbo
Too close to call on our weighted score (Llama-3.2-11B-Vision-Instruct 58, Jamba Mini 57, Qwen-MT Turbo 40). The right pick depends on what you value most.
AI21 LabsJamba Mini
57/100- ECI—
- Price$0.20 / $0.40
- Context256K
MetaLlama-3.2-11B-Vision-Instruct
58/100- ECI—
- Price$0.197 / $0.51
- Context128K
Alibaba (Qwen)Qwen-MT Turbo
40/100- ECI—
- Price$0.16 / $0.49
- Context16K
Too close to call
It is close. Our weighted score puts them within 1 points (Llama-3.2-11B-Vision-Instruct 58/100, Jamba Mini 57/100, Qwen-MT Turbo 40/100), so choose by what matters most for your work: Qwen-MT Turbo on price and Jamba Mini 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 priceQwen-MT TurboQwen-MT Turbo $0.242 · Jamba Mini $0.25 · Llama-3.2-11B-Vision-Instruct $0.275 per 1M tokens (3:1 blend)
- Longest contextJamba MiniJamba Mini 256,000 · Llama-3.2-11B-Vision-Instruct 128,000 · Qwen-MT Turbo 16,384 tokens
- Widest inputsLlama-3.2-11B-Vision-InstructJamba Mini: Text · Llama-3.2-11B-Vision-Instruct: Text, Images · Qwen-MT Turbo: Text
- Self-hostingJamba Mini and Llama-3.2-11B-Vision-InstructPublishes downloadable weights
| Measure | Weight | Jamba Mini | Llama-3.2-11B-Vision-Instruct | Qwen-MT Turbo |
|---|---|---|---|---|
| Price | 50% | 78 | 76 | 79 |
| Inputs & features | 30% | 35 | 50 | 0 |
| Context window | 20% | 36 | 24 | 0 |
| Overall | 100% | 57/100 | 58/100 | 40/100 |
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 | Jamba MiniAI21 Labs | Llama-3.2-11B-Vision-InstructMeta | Qwen-MT TurboAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.197 | $0.16 (best) |
| Output | $0.40 (best) | $0.51 | $0.49 |
| Cached input | — | — | — |
| Blended (3:1) | $0.25 | $0.275 | $0.242 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Median of 2 providers | Official Alibaba API |
| Limits | |||
| Context window | 256,000 tokens (best) | 128,000 tokens | 16,384 tokens |
| Max output | 4,096 tokens | 4,096 tokens | 8,192 tokens (best) |
| 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 | No | No |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | jamba-mini | — | qwen-mt-turbo |
| API providers | 1 | 2 (best) | 1 |
| Released | Jan 1, 2026 | Sep 25, 2024 | Jan 2025 |
| Knowledge cutoff | Aug 22, 2024 | Dec 2023 | Apr 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 Mini$2.80
- Llama-3.2-11B-Vision-Instruct$2.99
- Qwen-MT Turbo$2.58
Which should you choose?
Which is better: Jamba Mini, Llama-3.2-11B-Vision-Instruct or Qwen-MT Turbo?
It is close. Our weighted score puts them within 1 points (Llama-3.2-11B-Vision-Instruct 58/100, Jamba Mini 57/100, Qwen-MT Turbo 40/100), so choose by what matters most for your work: Qwen-MT Turbo on price and Jamba Mini 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, Jamba Mini, Llama-3.2-11B-Vision-Instruct or Qwen-MT Turbo?
Qwen-MT Turbo is cheaper at $0.16 input / $0.49 output per million tokens (official Alibaba API price). Jamba Mini costs $0.20 input / $0.40 output per million tokens (official AI21 Labs API price); Llama-3.2-11B-Vision-Instruct costs $0.197 input / $0.51 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.242 per million tokens for Qwen-MT Turbo versus $0.25 for Jamba Mini (1× as much) and $0.275 for Llama-3.2-11B-Vision-Instruct (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Jamba Mini has not been scored yet, Llama-3.2-11B-Vision-Instruct has not been scored yet and Qwen-MT Turbo has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Jamba Mini, Llama-3.2-11B-Vision-Instruct and Qwen-MT Turbo yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-MT Turbo does not support tool calling, which most coding agents need.
Which has the bigger context window?
Jamba Mini has the largest context window at 256,000 tokens, against 128,000 for Llama-3.2-11B-Vision-Instruct and 16,384 for Qwen-MT Turbo. Maximum output per response: Jamba Mini up to 4,096, Llama-3.2-11B-Vision-Instruct up to 4,096, Qwen-MT Turbo up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Jamba Mini accepts text; Llama-3.2-11B-Vision-Instruct accepts text and images; Qwen-MT Turbo accepts text. Llama-3.2-11B-Vision-Instruct handles the widest range of inputs.
Are any of these open source?
Jamba Mini and Llama-3.2-11B-Vision-Instruct publishes its weights and can be self-hosted; Qwen-MT Turbo is proprietary.
Which is newer?
Jamba Mini is the newest, released Jan 1, 2026. Qwen-MT Turbo came out Jan 2025; Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024. Knowledge cutoff: Jamba Mini Aug 22, 2024, Llama-3.2-11B-Vision-Instruct Dec 2023, Qwen-MT Turbo Apr 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.
