Laguna M.1 vs Llama 3.1 Nemotron Ultra 253B
Too close to call on our weighted score (Laguna M.1 68, Llama 3.1 Nemotron Ultra 253B 65). The right pick depends on what you value most.
PoolsideLaguna M.1
68/100- ECI—
- PriceFree / Free
- Context262K
NVIDIALlama 3.1 Nemotron Ultra 253B
65/100- ECI—
- PriceFree / Free
- Context128K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 3 points (Laguna M.1 68/100, Llama 3.1 Nemotron Ultra 253B 65/100), so choose by what matters most for your work: Laguna M.1 on price and Laguna M.1 for long inputs. 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 priceLaguna M.1 Free · Llama 3.1 Nemotron Ultra 253B Free per 1M tokens (3:1 blend)
- Longest contextLaguna M.1Laguna M.1 262,144 · Llama 3.1 Nemotron Ultra 253B 128,000 tokens
- Widest inputsSame inputsLaguna M.1: Text · Llama 3.1 Nemotron Ultra 253B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Laguna M.1 | Llama 3.1 Nemotron Ultra 253B |
|---|---|---|---|
| Price | 50% | 100 | 100 |
| Inputs & features | 30% | 35 | 35 |
| Context window | 20% | 37 | 24 |
| Overall | 100% | 68/100 | 65/100 |
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 | Laguna M.1Poolside | Llama 3.1 Nemotron Ultra 253BNVIDIA |
|---|---|---|
| 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 Poolside API | Official Nvidia API |
| Limits | ||
| Context window | 262,144 tokens (best) | 128,000 tokens |
| Max output | 32,768 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | poolside/laguna-m.1 | nvidia/llama-3.1-nemotron-ultra-253b-v1 |
| API providers | 2 (best) | 1 |
| Released | Apr 28, 2026 | Apr 7, 2025 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Laguna M.1Free
- Llama 3.1 Nemotron Ultra 253BFree
Which should you choose?
Which is better: Laguna M.1 or Llama 3.1 Nemotron Ultra 253B?
It is close. Our weighted score puts them within 3 points (Laguna M.1 68/100, Llama 3.1 Nemotron Ultra 253B 65/100), so choose by what matters most for your work: Laguna M.1 on price and Laguna M.1 for long inputs. 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, Laguna M.1 or Llama 3.1 Nemotron Ultra 253B?
Laguna M.1 and Llama 3.1 Nemotron Ultra 253B cost the same: Free input / Free output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Laguna M.1 has not been scored yet and Llama 3.1 Nemotron Ultra 253B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Laguna M.1 and Llama 3.1 Nemotron Ultra 253B 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?
Laguna M.1 has the largest context window at 262,144 tokens, against 128,000 for Llama 3.1 Nemotron Ultra 253B. Maximum output per response: Laguna M.1 up to 32,768, Llama 3.1 Nemotron Ultra 253B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Laguna M.1 accepts text; Llama 3.1 Nemotron Ultra 253B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Laguna M.1 is the newest, released Apr 28, 2026. Llama 3.1 Nemotron Ultra 253B came out Apr 7, 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.
