GLM-4.5-Flash vs Llama 3.1 Nemotron Ultra 253B vs North Mini Code
North Mini Code comes out ahead, 71 to 65 and 65 on our weighted score.
Z.ai (Zhipu)GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
NVIDIALlama 3.1 Nemotron Ultra 253B
65/100- ECI—
- PriceFree / Free
- Context128K
- Our pick
CohereNorth Mini Code
71/100- ECI—
- PriceFree / Free
- Context256K
North Mini Code is our pick
North Mini Code is the better all-round choice, scoring 71/100 against GLM-4.5-Flash (65) and Llama 3.1 Nemotron Ultra 253B (65). 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 priceSame priceGLM-4.5-Flash Free · Llama 3.1 Nemotron Ultra 253B Free · North Mini Code Free per 1M tokens (3:1 blend)
- Longest contextNorth Mini CodeNorth Mini Code 256,000 · GLM-4.5-Flash 131,072 · Llama 3.1 Nemotron Ultra 253B 128,000 tokens
- Widest inputsSame inputsGLM-4.5-Flash: Text · Llama 3.1 Nemotron Ultra 253B: Text · North Mini Code: Text
- Self-hostingLlama 3.1 Nemotron Ultra 253B and North Mini CodePublishes downloadable weights
| Measure | Weight | GLM-4.5-Flash | Llama 3.1 Nemotron Ultra 253B | North Mini Code |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 35 | 35 | 45 |
| Context window | 20% | 24 | 24 | 36 |
| Overall | 100% | 65/100 | 65/100 | 71/100 |
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-4.5-FlashZ.ai (Zhipu) | Llama 3.1 Nemotron Ultra 253BNVIDIA | North Mini CodeCohere |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | Free | Free | Free |
| Output | Free | Free | Free |
| Cached input | — | — | — |
| Blended (3:1) | Free | Free | Free |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Nvidia API | Official Cohere API |
| Limits | |||
| Context window | 131,072 tokens | 128,000 tokens | 256,000 tokens (best) |
| Max output | 98,304 tokens (best) | 8,192 tokens | 64,000 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 | Yes | Yes | Yeshigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | glm-4.5-flash | nvidia/llama-3.1-nemotron-ultra-253b-v1 | north-mini-code-1-0 |
| API providers | 4 (best) | 1 | 2 |
| Released | Jul 28, 2025 | Apr 7, 2025 | Jun 9, 2026 |
| Knowledge cutoff | Apr 2025 | — | Sep 23, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.5-FlashFree
- Llama 3.1 Nemotron Ultra 253BFree
- North Mini CodeFree
Which should you choose?
Which is better: GLM-4.5-Flash, Llama 3.1 Nemotron Ultra 253B or North Mini Code?
North Mini Code is the better all-round choice, scoring 71/100 against GLM-4.5-Flash (65) and Llama 3.1 Nemotron Ultra 253B (65). 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, GLM-4.5-Flash, Llama 3.1 Nemotron Ultra 253B or North Mini Code?
GLM-4.5-Flash, Llama 3.1 Nemotron Ultra 253B and North Mini Code cost the same: Free input / Free output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5-Flash has not been scored yet, Llama 3.1 Nemotron Ultra 253B has not been scored yet and North Mini Code has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Flash, Llama 3.1 Nemotron Ultra 253B and North Mini Code 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?
North Mini Code has the largest context window at 256,000 tokens, against 131,072 for GLM-4.5-Flash and 128,000 for Llama 3.1 Nemotron Ultra 253B. Maximum output per response: GLM-4.5-Flash up to 98,304, Llama 3.1 Nemotron Ultra 253B up to 8,192, North Mini Code up to 64,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Flash accepts text; Llama 3.1 Nemotron Ultra 253B accepts text; North Mini Code accepts text. They handle the same number of input types.
Are any of these open source?
Llama 3.1 Nemotron Ultra 253B and North Mini Code publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.
Which is newer?
North Mini Code is the newest, released Jun 9, 2026. GLM-4.5-Flash came out Jul 28, 2025; Llama 3.1 Nemotron Ultra 253B came out Apr 7, 2025. Knowledge cutoff: GLM-4.5-Flash Apr 2025, North Mini Code Sep 23, 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.
