Jamba Large vs Claude Sonnet 5.5 vs Qwen MT Plus
Claude Sonnet 5.5 comes out ahead, 46 to 29 and 11 on our weighted score, though Jamba Large is 13% cheaper per token.
AI21 LabsJamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
- Our pick
AnthropicClaude Sonnet 5.5
46/100- ECI166.7
- Price$2.00 / $10.00
- Context1M
Alibaba (Qwen)Qwen MT Plus
11/100- ECI—
- Price$2.46 / $7.37
- Context16K
Claude Sonnet 5.5 is our pick
Claude Sonnet 5.5 is the better all-round choice, scoring 46/100 against Jamba Large (29) and Qwen MT Plus (11). 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 priceJamba LargeJamba Large $3.50 · Qwen MT Plus $3.69 · Claude Sonnet 5.5 $4.00 per 1M tokens (3:1 blend)
- Longest contextClaude Sonnet 5.5Claude Sonnet 5.5 1,000,000 · Jamba Large 256,000 · Qwen MT Plus 16,384 tokens
- Widest inputsClaude Sonnet 5.5Jamba Large: Text · Claude Sonnet 5.5: Text, Images, PDFs · Qwen MT Plus: Text
- Self-hostingJamba LargePublishes downloadable weights
| Measure | Weight | Jamba Large | Claude Sonnet 5.5 | Qwen MT Plus |
|---|---|---|---|---|
| Price | 50% | 23 | 20 | 22 |
| Inputs & features | 30% | 35 | 80 | 0 |
| Context window | 20% | 36 | 60 | 0 |
| Overall | 100% | 29/100 | 46/100 | 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 | Jamba LargeAI21 Labs | Claude Sonnet 5.5Anthropic | Qwen MT PlusAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 166.7 | — |
| ECI rank | — | #5 of 165 | — |
| GPQA DiamondGraduate-level science questions | — | 95.6% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 88.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 100% | — |
| SimpleQA VerifiedShort factual questions | — | 46.5% | — |
| Price per million tokens | |||
| Input | $2.00 (best) | $2.00 (best) | $2.46 |
| Output | $8.00 | $10.00 | $7.37 (best) |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $3.50 (best) | $4.00 | $3.69 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Official Anthropic API | Official Alibaba API |
| Limits | |||
| Context window | 256,000 tokens | 1,000,000 tokens (best) | 16,384 tokens |
| Max output | 4,096 tokens | 128,000 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yeslow · medium · high · xhigh · max | No |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | jamba-large | claude-sonnet-5-5 | qwen-mt-plus |
| API providers | 1 | 34 (best) | 3 |
| Released | Jul 3, 2025 | Sep 28, 2026 | Jul 24, 2025 |
| Knowledge cutoff | Aug 22, 2024 | Jun 2026 | — |
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
- Claude Sonnet 5.5$40.00
- Qwen MT Plus$39.34
Which should you choose?
Which is better: Jamba Large, Claude Sonnet 5.5 or Qwen MT Plus?
Claude Sonnet 5.5 is the better all-round choice, scoring 46/100 against Jamba Large (29) and Qwen MT Plus (11). 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, Jamba Large, Claude Sonnet 5.5 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); Claude Sonnet 5.5 costs $2.00 input / $10.00 output per million tokens (official Anthropic 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) and $4.00 for Claude Sonnet 5.5 (1.1× 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, Claude Sonnet 5.5 has an ECI of 166.7 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, Claude Sonnet 5.5 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?
Claude Sonnet 5.5 has the largest context window at 1,000,000 tokens, against 256,000 for Jamba Large and 16,384 for Qwen MT Plus. Maximum output per response: Jamba Large up to 4,096, Claude Sonnet 5.5 up to 128,000, Qwen MT Plus up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Jamba Large accepts text; Claude Sonnet 5.5 accepts text, images and PDFs; Qwen MT Plus accepts text. Claude Sonnet 5.5 handles the widest range of inputs.
Are any of these open source?
Jamba Large publishes its weights and can be self-hosted; Claude Sonnet 5.5 and Qwen MT Plus is proprietary.
Which is newer?
Claude Sonnet 5.5 is the newest, released Sep 28, 2026. Qwen MT Plus came out Jul 24, 2025; Jamba Large came out Jul 3, 2025. Knowledge cutoff: Jamba Large Aug 22, 2024, Claude Sonnet 5.5 Jun 2026.
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.
