GLM-4.5V vs Jamba Large vs Qwen MT Plus
GLM-4.5V comes out ahead, 48 to 29 and 11 on our weighted score, and it is the cheaper option too.
- Our pick
Z.ai (Zhipu)GLM-4.5V
48/100- ECI—
- Price$0.60 / $1.80
- Context64K
AI21 LabsJamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
Alibaba (Qwen)Qwen MT Plus
11/100- ECI—
- Price$2.46 / $7.37
- Context16K
GLM-4.5V is our pick
GLM-4.5V is the better all-round choice, scoring 48/100 against Jamba Large (29) and Qwen MT Plus (11). It leads on price and inputs & features. Jamba Large wins on 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 priceGLM-4.5VGLM-4.5V $0.90 · Jamba Large $3.50 · Qwen MT Plus $3.69 per 1M tokens (3:1 blend)
- Longest contextJamba LargeJamba Large 256,000 · GLM-4.5V 64,000 · Qwen MT Plus 16,384 tokens
- Widest inputsGLM-4.5VGLM-4.5V: Text, Images, Video · Jamba Large: Text · Qwen MT Plus: Text
- Self-hostingGLM-4.5V and Jamba LargePublishes downloadable weights
| Measure | Weight | GLM-4.5V | Jamba Large | Qwen MT Plus |
|---|---|---|---|---|
| Price | 50% | 50 | 23 | 22 |
| Inputs & features | 30% | 70 | 35 | 0 |
| Context window | 20% | 12 | 36 | 0 |
| Overall | 100% | 48/100 | 29/100 | 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 | GLM-4.5VZ.ai (Zhipu) | Jamba LargeAI21 Labs | Qwen MT PlusAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 (best) | $2.00 | $2.46 |
| Output | $1.80 (best) | $8.00 | $7.37 |
| Cached input | $0.11 | — | — |
| Blended (3:1) | $0.90 (best) | $3.50 | $3.69 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official AI21 Labs API | Official Alibaba API |
| Limits | |||
| Context window | 64,000 tokens | 256,000 tokens (best) | 16,384 tokens |
| Max output | 16,384 tokens (best) | 4,096 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.5v | jamba-large | qwen-mt-plus |
| API providers | 17 (best) | 1 | 3 |
| Released | Aug 11, 2025 | Jul 3, 2025 | Jul 24, 2025 |
| Knowledge cutoff | 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.
- GLM-4.5V$9.60
- Jamba Large$36.00
- Qwen MT Plus$39.34
Which should you choose?
Which is better: GLM-4.5V, Jamba Large or Qwen MT Plus?
GLM-4.5V is the better all-round choice, scoring 48/100 against Jamba Large (29) and Qwen MT Plus (11). It leads on price and inputs & features. Jamba Large wins on 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, GLM-4.5V, Jamba Large or Qwen MT Plus?
GLM-4.5V is cheaper at $0.60 input / $1.80 output per million tokens (official Z.AI API price). Jamba Large costs $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 $0.90 per million tokens for GLM-4.5V versus $3.50 for Jamba Large (3.9× as much) and $3.69 for Qwen MT Plus (4.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5V has not been scored yet, Jamba Large 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 GLM-4.5V, Jamba Large 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 64,000 for GLM-4.5V and 16,384 for Qwen MT Plus. Maximum output per response: GLM-4.5V up to 16,384, Jamba Large up to 4,096, Qwen MT Plus up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5V accepts text, images and video; Jamba Large accepts text; Qwen MT Plus accepts text. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5V and Jamba Large publishes its weights and can be self-hosted; Qwen MT Plus is proprietary.
Which is newer?
GLM-4.5V is the newest, released Aug 11, 2025. Qwen MT Plus came out Jul 24, 2025; Jamba Large came out Jul 3, 2025. Knowledge cutoff: GLM-4.5V 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.
