R1 Distill Llama 70B — DeepSeek | Modeldex

R1 Distill Llama 70B

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DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across...

Updated 4 days agoStructured data from Modeldex catalog

Budget

Knowledge cutoff

Jul 31, 2024(1.7 years ago)

API release

Jan 23, 2025(1.2 years ago)

Not enough benchmark coverage yet for an Intelligence Index — needs at least 3 results across 2 categories.

Overview

History

R1 Distill Llama 70B became available via the DeepSeek API on 2025-01-23.

Training & availability

Training data has a knowledge cutoff of 2024-07-31 — information about events after that date is unlikely to appear in the model's responses. DeepSeek has not released the underlying model weights — access is via their hosted API only.

Capabilities

Context window: 131K tokens.
Input modalities: text.

Recommended for: cheap.

Limitations

The knowledge cutoff is 20 months old — this model will not know about recent events, releases, or API changes.
Text-only — cannot process images, audio, or video inputs.

Pricing

Input: $0.7000 per 1M tokens
Output: $0.8000 per 1M tokens

Use the cost calculator above to estimate monthly spend for your workload.

Quick start

Minimal example using the OpenRouter API. Copy, paste, replace the key.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="sk-or-...",
)
resp = client.chat.completions.create(
    model="deepseek/deepseek-r1-distill-llama-70b",
    messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(resp.choices[0].message.content)

Cost calculator

Estimate your monthly bill. Presets are typical workload sizes.

Input tokens / month5.0M

@ $0.7/1M

Output tokens / month2.0M

@ $0.8/1M

Input cost

$3.5

5.0M × $0.7/1M

Output cost

$1.6

2.0M × $0.8/1M

Total / month

$5.1

$61.2 / year

Providers & performance

2 providers

Multi-provider inference routes for this model — sorted by throughput. Latency is time-to-first-token; throughput is output tokens per second. Data from OpenRouter, measured over the last 30 minutes.

Provider	Throughput	Latency (TTFT)	Input $ / 1M	Output $ / 1M	Context	Quant	Supports
DeepInfra	47tok/s	378ms	$0.7	$0.8	131K	fp8	json
Novita	46tok/s	474ms	$0.8	$0.8	8K	bf16	—

Popularity

Signals from open-source communities — not a quality measure, but useful for gauging adoption among developers.

🤗

HuggingFace downloads

150.2K/ month

HuggingFace likes

767

Integrations & tooling support

Tool calling: Not supported
Structured outputs: Not supported

Price vs quality

Budget pricing

Priced low — good for high-volume tasks. Quality tier pending more benchmark coverage.