Jamba Large vs GLM-4.5V
GLM-4.5V comes out ahead, 48 to 29 on our weighted score, and it is the cheaper option too.
AI21 LabsJamba Large
29/100- ECI—
- Price$2.00 / $8.00
- Context256K
- Our pick
Z.ai (Zhipu)GLM-4.5V
48/100- ECI—
- Price$0.60 / $1.80
- Context64K
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Make it a three-way comparison.
GLM-4.5V is our pick
GLM-4.5V is the better all-round choice, scoring 48/100 against Jamba Large (29). 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 per 1M tokens (3:1 blend)
- Longest contextJamba LargeJamba Large 256,000 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VJamba Large: Text · GLM-4.5V: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Jamba Large | GLM-4.5V |
|---|---|---|---|
| Price | 50% | 23 | 50 |
| Inputs & features | 30% | 35 | 70 |
| Context window | 20% | 36 | 12 |
| Overall | 100% | 29/100 | 48/100 |
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 | GLM-4.5VZ.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $2.00 | $0.60 (best) |
| Output | $8.00 | $1.80 (best) |
| Cached input | — | $0.11 |
| Blended (3:1) | $3.50 | $0.90 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Official Z.AI API |
| Limits | ||
| Context window | 256,000 tokens (best) | 64,000 tokens |
| Max output | 4,096 tokens | 16,384 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | Yes |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | jamba-large | glm-4.5v |
| API providers | 1 | 17 (best) |
| Released | Jul 3, 2025 | Aug 11, 2025 |
| Knowledge cutoff | Aug 22, 2024 | Apr 2025 |
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
- GLM-4.5V$9.60
Which should you choose?
Which is better: Jamba Large or GLM-4.5V?
GLM-4.5V is the better all-round choice, scoring 48/100 against Jamba Large (29). 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, Jamba Large or GLM-4.5V?
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). 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).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Jamba Large has not been scored yet and GLM-4.5V has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Jamba Large and GLM-4.5V yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Jamba Large has the largest context window at 256,000 tokens, against 64,000 for GLM-4.5V. Maximum output per response: Jamba Large up to 4,096, GLM-4.5V up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Jamba Large accepts text; GLM-4.5V accepts text, images and video. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
GLM-4.5V is the newest, released Aug 11, 2025. Jamba Large came out Jul 3, 2025. Knowledge cutoff: Jamba Large Aug 22, 2024, GLM-4.5V Apr 2025.
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.
