Llama 3.3 Euryale 70B
Sao10K · released Dec 7, 2024 · Sao10K/L3.3-70B-Euryale-v2.3
- Type
- Open weightsLlama 3 Community License
- Params
- 70.6B
- Context
- 131K
about 98K words of context · download allowed, licence restricts use
Our take
Written Aug 3, 2026Llama 3.3 Euryale 70B is a 70.6-billion-parameter text model from the Sao10K community with a 131,072-token request limit. Released under Meta's Llama 3 Community License, it is a long-context option for document work where licence terms are acceptable, though no quality scores are available yet.
Pick this for long-document processing at 131,072 tokens when the Llama 3 Community License terms work for your use case. It is a budget-conscious choice with identical rates across both of its two providers. Skip it if you need measured quality benchmarks, fast generation speed, or a busier hosting market with price competition.
The case for it
- 131,072-token request limit — among the longest in the 70-billion-parameter class we track.
- Commercial use permitted under the Llama 3 Community License, with specific attribution requirements.
The case against it
- No measured benchmark scores in our data — no Elo, MMLU, or other quality scores are listed.
- Slow throughput on the only measured provider, at 8 tokens per second.
- Only two tracked offers, with no cheaper tier available across either provider.
How good is it?
We hold no score for this model.
We look for every model we track on every board we watch, and none of them has turned up Llama 3.3 Euryale 70B — so there is no intelligence, coding, agentic or writing score to show you, not a low one, none.
Can you run it yourself?
- Fits in memory
- weights load entirely on the card
- Spills to system RAM
- some weights offload; much slower
- Too large
- will not load even with offload
- est
- size is calculated; the verdict could change by 10%
GeForce RTX 4090 · 24 GB
Too large for this card. The weights do not fit even with part of them offloaded to system memory.
Apple M1 Pro (16-core GPU) · 32 GB
Too large for this card. The weights do not fit even with part of them offloaded to system memory.
Apple M1 Max (32-core GPU) · 64 GB
Borderline fit on an estimated size. It leaves 0.3 GB spare on a size we calculated rather than measured, and a 10% error either way would change the answer.
Memory use by level
Against a 24 GB card.
All 3 sizes here are calculated, not measured. We hold no measured file for this model, so each size comes from the parameter count and every verdict above inherits that uncertainty.
Check against your own machine → · All 71 devices, with every size →
Or rent it from someone else
Cheapest of 2 live listings. Picked at the widest standard context we hold, within one quantisation slice, so the numbers beside it are a price one host actually charges.
- per 1M tokens
- $0.65 in / $0.75 out
- Context served
- 131K
- Throughput
- Not measured
| Provider | In / out per 1M tokens | Context | Throughput | Trains on prompts | Logs prompts | Zero retention |
|---|---|---|---|---|---|---|
| OpenRouter | $0.65 / $0.75 | 131K | not measured | Unknown | Unknown | Unknown |
| NextBitbf16 | $0.65 / $0.75 | 131K | 7 tok/s | No | No | Confirmed |
Across the 2 listings we hold: 1 say they do not train on prompts, 0 say they do and 1 do not say. 1 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.
What each host's API supports
From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.
- ✓
- Supported
- ✗
- Not supported
- Not published
- host gave no parameter list
| Provider | Tool calling | JSON output | Strict schema |
|---|---|---|---|
| OpenRouter | ✗ | ✓ | ✓ |
| NextBitbf16 | ✗ | ✓ | ✓ |
Tool calling: 0 of 2 listings say yes, 2 say no. JSON output: 2 of 2 listings say yes. Strict schema: 2 of 2 listings say yes.
Models people weigh against Llama 3.3 Euryale 70B
When we formed this view
Dates behind this page
Prices last checked 4d ago
What we do not know about this model yet
- We hold no measured file for it, so all 3 sizes on this page are calculated from the parameter count.
- No board we watch has turned up a score, so we hold no quality figures at all.
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
- 1 of 2 listings do not say whether they train on prompts.
- We hold no cached-input rate for any of its listings.
Licence and identifiers
What the licence allowsLlama 3 Community License, what it allows commercially, and the identifiers you need to pull this model — its Hugging Face repo, our slug and a machine-readable card.
Licence
Llama 3 Community License
Commercial use allowed below 700M MAU; requires "Built with Meta Llama 3" attribution and Llama naming on derivatives.
Identifiers
- Hugging Face
- Sao10K/L3.3-70B-Euryale-v2.3
- Architecture
- Dense
- Modality record
- text->text
- Catalogue slug
- sao10k-llama-3-3-euryale-70b