DeepSeek AI DeepSeek R1 Distill Llama 70B
Nebius chatDeepSeek 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.
Estimate DeepSeek AI DeepSeek R1 Distill Llama 70B spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
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.
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.
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"))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.
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.
Third-party evals — verify the marketing.
Cross-check our number against the rest of the ecosystem.