Last refreshed 2026-05-22. Next refresh: weekly.
Why use DeepSeek V3.1 on Fireworks AI?
Fireworks AI offers DeepSeek V3.1 with pay-as-you-go pricing at $0.56/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Compare DeepSeek V3.1 across 9 providers to find the best fit for your use caseInput / 1M
$0.56
Output / 1M
$1.68
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install openaiAuth
export FIREWORKS_API_KEY=...Call
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],Model ID
accounts/fireworks/models/deepseek-v3p1Request example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/deepseek-v3p1",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/deepseek-v3p1", not the LLMReference slug "deepseek-v3.1".
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Compare DeepSeek V3.1 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Microsoft Foundry | — | — |
| Fireworks AI | $0.56 | $1.68 |
| NVIDIA NIM | — | — |
| Together AI | $0.60 | $1.70 |
| AWS Bedrock | $0.60 | $1.73 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.56 |
| Output tokens | $1.68 |
Capabilities
VisionMultimodalStructured OutputsCode Execution
About DeepSeek V3.1
Enhanced reasoning and grounded retrieval model from DeepSeek with multimodal text and image understanding.
Get Started
Model Specs
Released2025-08-21
Parameters671B total, 37B active (MoE)
Context64k
ArchitectureMixture of Experts