DeepSeek · LLM API pricing
deepseek-r1-distill-qwen-1.5b API pricing: cheapest provider
2 providers sell deepseek-r1-distill-qwen-1.5b. Nscale is cheapest; the most expensive charges 1.1× as much for the same model.
- Cheapest$0.09per 1M · Nscale
- Input · output$0.09 / $0.09per 1M tokens
- Price gap1.1×across 2 providers
- Accuracy33.6%GPQA
- Context131Kmax tokens
Standard list prices in USD from each provider's pricing page · last price change Sep 28, 2026 · How we collect and rank prices
Ranked for your volume
deepseek-r1-distill-qwen-1.5b monthly cost by provider
Change the monthly tokens and the ranking updates instantly, using each provider's standard list price.
More requirements: caching, context, features, provider
| Provider | Estimated / month | Input / 1M | Output / 1M | Context |
|---|---|---|---|---|
1 NscaleInference provider - lowest for your volumePricing page | $1.08 | $0.09 | $0.09 | Not listed |
2 Fireworks AIInference providerPricing page | $1.20 | $0.10 | $0.10 | 131,072 |
Order depends on listed price for your volume only. No provider pays for its position.
Input volume includes the cached share, not an additional token volume. This is a list-price estimate, not a quote: cache-write charges, cache eligibility/TTL, batch discounts, long-context surcharges, regional pricing and taxes are excluded. Check the provider's terms for your workload before switching.
Accuracy: GPQA Diamond (graduate-level science questions) measured by Epoch AI (CC BY 4.0) on DeepSeek-R1-Distill-Qwen-1.5B, run Aug 28, 2026. The model is the same at every provider, though quantized deployments can score lower.
Price history
The cheapest price has not changed since tracking started on Sep 28, 2026: $0.09 per 1M tokens at Nscale. All price changes
Switch to the cheapest provider
Already using the OpenAI SDK? Change the base URL, key and model name:
from openai import OpenAI
import os
client = OpenAI(
base_url="https://inference.api.nscale.com/v1",
api_key=os.environ["NSCALE_SERVICE_TOKEN"],
)
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
messages=[{"role": "user", "content": "Hello"}],
)Compare deepseek-r1-distill-qwen-1.5b with another model
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