Llama 3.1 Nemotron Ultra 253B vs Vision Large vs GLM-4.5-Flash
Vision Large comes out ahead, 84 to 31 and 31 on our weighted score.
NVIDIALlama 3.1 Nemotron Ultra 253B
31/100- ECI—
- PriceFree / Free
- Context128K
- Our pick
VisparkVision Large
84/100- ECI—
- Price—
- Context1M
Z.ai (Zhipu)GLM-4.5-Flash
31/100- ECI—
- PriceFree / Free
- Context131K
Vision Large is our pick
Vision Large is the better all-round choice, scoring 84/100 against GLM-4.5-Flash (31) and Llama 3.1 Nemotron Ultra 253B (31). 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 priceLlama 3.1 Nemotron Ultra 253B and GLM-4.5-FlashLlama 3.1 Nemotron Ultra 253B Free · GLM-4.5-Flash Free per 1M tokens (3:1 blend) · Vision Large unpriced
- Longest contextVision LargeVision Large 1,000,000 · GLM-4.5-Flash 131,072 · Llama 3.1 Nemotron Ultra 253B 128,000 tokens
- Widest inputsVision LargeLlama 3.1 Nemotron Ultra 253B: Text · Vision Large: Text, Images, PDFs, Audio, Video · GLM-4.5-Flash: Text
- Self-hostingLlama 3.1 Nemotron Ultra 253BPublishes downloadable weights
| Measure | Weight | Llama 3.1 Nemotron Ultra 253B | Vision Large | GLM-4.5-Flash |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 100 | 35 |
| Context window | 40% | 24 | 60 | 24 |
| Overall | 100% | 31/100 | 84/100 | 31/100 |
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 | Llama 3.1 Nemotron Ultra 253BNVIDIA | Vision LargeVispark | GLM-4.5-FlashZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | Free | — | Free |
| Output | Free | — | Free |
| Cached input | — | — | — |
| Blended (3:1) | Free | — | Free |
| Long-context rate | Same rate | — | Same rate |
| Price source | Official Nvidia API | — | Official Z.AI API |
| Limits | |||
| Context window | 128,000 tokens | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 8,192 tokens | 65,536 tokens | 98,304 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | nvidia/llama-3.1-nemotron-ultra-253b-v1 | — | glm-4.5-flash |
| API providers | 1 | — | 4 (best) |
| Released | Apr 7, 2025 | May 15, 2024 | Jul 28, 2025 |
| Knowledge cutoff | — | — | 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.
- Llama 3.1 Nemotron Ultra 253BFree
- Vision Large—
- GLM-4.5-FlashFree
Which should you choose?
Which is better: Llama 3.1 Nemotron Ultra 253B, Vision Large or GLM-4.5-Flash?
Vision Large is the better all-round choice, scoring 84/100 against GLM-4.5-Flash (31) and Llama 3.1 Nemotron Ultra 253B (31). 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, Llama 3.1 Nemotron Ultra 253B, Vision Large or GLM-4.5-Flash?
Llama 3.1 Nemotron Ultra 253B is cheaper at Free input / Free output per million tokens (official Nvidia API price). GLM-4.5-Flash costs Free input / Free output per million tokens (official Z.AI API price). Llama 3.1 Nemotron Ultra 253B is listed as free. Vision Large has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama 3.1 Nemotron Ultra 253B has not been scored yet, Vision Large has not been scored yet and GLM-4.5-Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama 3.1 Nemotron Ultra 253B, Vision Large and GLM-4.5-Flash yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Vision Large has the largest context window at 1,000,000 tokens, against 131,072 for GLM-4.5-Flash and 128,000 for Llama 3.1 Nemotron Ultra 253B. Maximum output per response: Llama 3.1 Nemotron Ultra 253B up to 8,192, Vision Large up to 65,536, GLM-4.5-Flash up to 98,304 tokens.
Which can read images, PDFs, audio or video?
Llama 3.1 Nemotron Ultra 253B accepts text; Vision Large accepts text, images, PDFs, audio and video; GLM-4.5-Flash accepts text. Vision Large handles the widest range of inputs.
Are any of these open source?
Llama 3.1 Nemotron Ultra 253B publishes its weights and can be self-hosted; Vision Large and GLM-4.5-Flash is proprietary.
Which is newer?
GLM-4.5-Flash is the newest, released Jul 28, 2025. Llama 3.1 Nemotron Ultra 253B came out Apr 7, 2025; Vision Large came out May 15, 2024. Knowledge cutoff: GLM-4.5-Flash 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 Oct 4, 2026.
