Jamba Large vs Sarvam-M vs Qwen MT Plus
Jamba Large comes out ahead, 35 to 6 and 0 on our weighted score, and it is the cheaper option too.
- Our pick
AI21 LabsJamba Large
35/100- ECI—
- Price$2.00 / $8.00
- Context256K
Sarvam AI
Sarvam-M
6/100- ECI—
- Price—
- Context33K
Alibaba (Qwen)Qwen MT Plus
0/100- ECI—
- Price$2.46 / $7.37
- Context16K
Jamba Large is our pick
Jamba Large is the better all-round choice, scoring 35/100 against Sarvam-M (6) and Qwen MT Plus (0). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 per 1M tokens (3:1 blend) · Sarvam-M unpriced
- Longest contextJamba LargeJamba Large 256,000 · Sarvam-M 32,768 · Qwen MT Plus 16,384 tokens
- Widest inputsSame inputsJamba Large: Text · Sarvam-M: Text · Qwen MT Plus: Text
- Self-hostingJamba Large and Sarvam-MPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Jamba Large | Sarvam-M | Qwen MT Plus |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 10 | 0 |
| Context window | 40% | 36 | 0 | 0 |
| Overall | 100% | 35/100 | 6/100 | 0/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Jamba LargeAI21 Labs | Sarvam-MSarvam AI | Qwen MT PlusAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.00 (best) | — | $2.46 |
| Output | $8.00 | — | $7.37 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $3.50 (best) | — | $3.69 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Official AI21 Labs API | — | Official Alibaba API |
| Limits | |||
| Context window | 256,000 tokens (best) | 32,768 tokens | 16,384 tokens |
| Max output | 4,096 tokens | 32,768 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | No | No |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | jamba-large | — | qwen-mt-plus |
| API providers | 1 | — | 3 (best) |
| Released | Jul 3, 2025 | May 20, 2025 | Jul 24, 2025 |
| Knowledge cutoff | 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.
- Jamba Large$36.00
- Sarvam-M—
- Qwen MT Plus$39.34
Which should you choose?
Which is better: Jamba Large, Sarvam-M or Qwen MT Plus?
Jamba Large is the better all-round choice, scoring 35/100 against Sarvam-M (6) and Qwen MT Plus (0). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Jamba Large, Sarvam-M 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). 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). Sarvam-M has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Jamba Large has not been scored yet, Sarvam-M 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, Sarvam-M 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 Sarvam-M and 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 32,768 for Sarvam-M and 16,384 for Qwen MT Plus. Maximum output per response: Jamba Large up to 4,096, Sarvam-M up to 32,768, Qwen MT Plus up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Jamba Large accepts text; Sarvam-M accepts text; Qwen MT Plus accepts text. They handle the same number of input types.
Are any of these open source?
Jamba Large and Sarvam-M publishes its weights (Apache 2.0) and can be self-hosted; 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; Sarvam-M came out May 20, 2025. Knowledge cutoff: 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.
