Llama 3.1 Swallow 70B Instruct
llama-3.1-swallow-70b-instruct
Last refreshed 2026-05-01. Next refresh: weekly.
Llama 3.1 Swallow 70B Instruct is worth evaluating for general LLM work when its provider route and context window match the workload.
Decision context: Coding task fit, 1 tracked provider route, and research from 2026-01-01.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 4K context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
Cheapest output
-
NVIDIA NIM per 1M tokens
Provider routes
1
Tracked API hosts
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-01-01
Researched 137d ago
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| NVIDIA NIM | - | - | ServerlessPartial |
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
Japanese bilingual model from Institute of Science Tokyo, fine-tuned from Llama 3.1.
Llama 3.1 Swallow 70B Instruct has a 4K-token context window.
Capabilities
No model capability flags are currently sourced.
