DeepSeek AI DeepSeek R1 Distill Llama 70B

Nebius chat

DeepSeek AI DeepSeek R1 Distill Llama 70B is a Nebius chat model.It supports a 128,000-token context windowwith up to 128,000 output tokens.Input is priced at $0.250/M tokens and output at $0.750/M tokens. Capabilities include function calling. Route DeepSeek AI DeepSeek R1 Distill Llama 70B via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: May 12, 2026 View source ↗
Cost calculator

Estimate DeepSeek AI DeepSeek R1 Distill Llama 70B spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
0128,000
400
0128,000
5,000
01,000,000
Per request
$0.001050
in $0.000750 · out $0.000300
Per day
$5.25
5,000 requests
Per month
$160
152,188 requests

Estimate uses $0.2500/M input · $0.7500/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.

Input $0.250/M
Output $0.750/M

Limits

Context window
128,000 tokens
Max input
128,000 tokens
Max output
128,000 tokens
Modalities
text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls — not advertised
  • Vision input — not advertised
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input — not advertised
  • Streaming ✓ supported
  • Structured output — not advertised
  • Prompt caching — not advertised
  • Reasoning — not advertised

Where it's strong

  • +agentic workflows that depend on reliable tool calls

Watch out for

  • !strict structured output — no JSON-schema enforcement, expect retry loops

Benchmarks pending

We haven't logged public benchmark scores for DeepSeek AI DeepSeek R1 Distill Llama 70B yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call DeepSeek AI DeepSeek R1 Distill Llama 70B via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# DeepSeek AI DeepSeek R1 Distill Llama 70B via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="nebius/deepseek-ai-deepseek-r1-distill-llama-70b",
    messages=[{"role": "user", "content": "Hello, DeepSeek AI DeepSeek R1 Distill Llama 70B!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="nebius/deepseek-ai-deepseek-r1-distill-llama-70b",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗

Same model on other providers

deepseek-ai-deepseek-r1-distill-llama-70b is also available via 2 other routes. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
DeepInfra$0.200/M$0.600/MMay 12, 2026
Nscale$0.375/M$0.375/MMay 12, 2026

Compare with similar models

DeepSeek AI DeepSeek R1 Distill Llama 70B doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark.

FAQ

How much does DeepSeek AI DeepSeek R1 Distill Llama 70B cost?

Input is priced at $0.250 per 1M tokens and output at $0.750 per 1M tokens (Nebius, last verified May 12, 2026).

What is the context window of DeepSeek AI DeepSeek R1 Distill Llama 70B?

DeepSeek AI DeepSeek R1 Distill Llama 70B supports a 128,000-token context window with up to 128,000 output tokens.

Does DeepSeek AI DeepSeek R1 Distill Llama 70B support function calling?

Yes — DeepSeek AI DeepSeek R1 Distill Llama 70B supports function (tool) calling.

Is DeepSeek AI DeepSeek R1 Distill Llama 70B good for production?

DeepSeek AI DeepSeek R1 Distill Llama 70B is well-suited for agentic workflows that depend on reliable tool calls. Consider alternatives if you need strict structured output — no JSON-schema enforcement, expect retry loops.

How can I route to DeepSeek AI DeepSeek R1 Distill Llama 70B with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for DeepSeek AI DeepSeek R1 Distill Llama 70B

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.