Qwen3 4B Instruct 2507 API Pricing
As of October 10, 2026, Qwen3 4B Instruct 2507 costs $0.20 per 1M input tokens and $0.20 per 1M output tokens on Fireworks AI. It has a 262,144-token context window and returns up to 262,144 tokens per response.
- Input
- $0.20 / 1M tokens
- Output
- $0.20 / 1M tokens
- Context window
- 262,144 tokens
- Max output
- 262,144 tokens
- Providers
- 2
- Added to LiteLLM
- October 2025
Qwen3 4B Instruct 2507 pricing by provider
2 listings across 2 providers. Token prices are in US dollars per 1M tokens. The highlighted row is the price quoted above.
| Provider | Model name in LiteLLM | Input | Output | Context |
|---|---|---|---|---|
| Fireworks AI | fireworks_ai/accounts/fireworks/models/qwen3-4b-instruct-2507 | $0.20 | $0.20 | 256K |
| Lemonadegguf | lemonade/Qwen3-4B-Instruct-2507-GGUF | $0 | $0 | 256K |
What Qwen3 4B Instruct 2507 costs in practice
1,000 requests with 2,000 input and 500 output tokens each
| Fireworks AI | $0.50 |
100 long-document requests with 100,000 input and 2,000 output tokens each
| Fireworks AI | $2.04 |
Qwen3 4B Instruct 2507 features
- Function calling
- Structured output
Use Qwen3 4B Instruct 2507 with LiteLLM
Call Qwen3 4B Instruct 2507 through the LiteLLM Python SDK, or put it behind the LiteLLM proxy and send OpenAI-format requests to /v1/chat/completions. LiteLLM tracks the cost of every request at these prices.
from litellm import completion
response = completion(
model="fireworks_ai/accounts/fireworks/models/qwen3-4b-instruct-2507",
messages=[{"role": "user", "content": "Hello!"}],
)model_list:
- model_name: qwen3-4b-instruct-2507
litellm_params:
model: fireworks_ai/accounts/fireworks/models/qwen3-4b-instruct-2507
api_key: os.environ/FIREWORKS_AI_API_KEYcurl http://0.0.0.0:4000/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-1234" \
-d '{
"model": "qwen3-4b-instruct-2507",
"messages": [{"role": "user", "content": "Hello!"}]
}'Qwen3 4B Instruct 2507 FAQ
How much does Qwen3 4B Instruct 2507 cost?
Qwen3 4B Instruct 2507 costs $0.20 per 1M input tokens and $0.20 per 1M output tokens on Fireworks AI.
What is the context window of Qwen3 4B Instruct 2507?
Qwen3 4B Instruct 2507 has a 262,144-token context window and returns up to 262,144 tokens per response.
Which providers offer Qwen3 4B Instruct 2507?
Qwen3 4B Instruct 2507 is available from 2 providers through LiteLLM: Fireworks AI and Lemonade.
How do I call Qwen3 4B Instruct 2507 with an OpenAI-compatible API?
Use the LiteLLM Python SDK with model="fireworks_ai/accounts/fireworks/models/qwen3-4b-instruct-2507", or add the model to the LiteLLM proxy's config.yaml and send requests to /v1/chat/completions from any OpenAI client. LiteLLM tracks the cost of every request at the prices on this page.
What features does Qwen3 4B Instruct 2507 support?
Qwen3 4B Instruct 2507 supports function calling and structured output.
When did LiteLLM add Qwen3 4B Instruct 2507?
Qwen3 4B Instruct 2507 was added to LiteLLM's model price file in October 2025.
Sources
Prices come from LiteLLM's open-source model_prices_and_context_window.json, which LiteLLM uses to calculate the cost of every request.
LiteLLM docs: Fireworks AI, Lemonade.
Provider pages: Fireworks AI, Lemonade.
