DeepSeek V4 Flash vs Qwen3-VL 8B
Two chat models compared on price, context, capabilities and measured speed. External prices are public list rates verified 2026-09-16; Inference APIs prices are live.
| DeepSeek V4 Flash | Qwen3-VL 8B | |
|---|---|---|
| Provider | DeepSeek | Alibaba Qwen |
| Model id | deepseek-ai/DeepSeek-V4-Flash | Qwen/Qwen3-VL-8B-Instruct |
| Input price | $0.19 / 1M tokens | $0.24 / 1M tokens |
| Output price | $0.38 / 1M tokens | $0.90 / 1M tokens |
| Context window | 1M tokens | 262K tokens |
| Capabilities | Chat, Reasoning, Coding, Tool calling, 1M context | Vision, Chat, OCR, Tool calling |
| Weights | Open | Open |
| Availability | Available on Inference APIs | Coming soon |
| Rate limits | No daily caps; pay per request | No daily caps; pay per request |
| Time to first token | 1.42 s | not measured |
| Output speed | 55 tokens / s | not measured |
Cost for 1M input + 1M output tokens
DeepSeek V4 Flash is about 50% cheaper for this workload at list price.
Measured speed
Speed figures for Inference APIs models are medians of three runs from a European client on 2026-09-16, against the public endpoint, using a ~120-word generation prompt (chat), a 300-character paragraph (speech) or a -second clip (transcription). External models are not measured here; treat "not measured" as unknown, not slow.
When to pick which
- DeepSeek V4 Flash — DeepSeek's fast, inexpensive V4 model with a 1M-token context. Strong general assistant and coding model at the lowest price per token here.
- Qwen3-VL 8B — Compact vision-language model for image understanding, OCR and screenshot reasoning.
Try DeepSeek V4 Flash
Same OpenAI request shape; the change is the base URL and key. Full parameters, aliases and pricing on the model page.
curl https://api.inferenceapis.com/v1/chat/completions \
-H "Authorization: Bearer $INFERENCE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-ai/DeepSeek-V4-Flash",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello! What can you do?"}
]
}'
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.inferenceapis.com/v1",
api_key=os.environ["INFERENCE_API_KEY"],
)
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V4-Flash",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello! What can you do?"},
],
)
print(response.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.inferenceapis.com/v1",
apiKey: process.env.INFERENCE_API_KEY,
});
const response = await client.chat.completions.create({
model: "deepseek-ai/DeepSeek-V4-Flash",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Hello! What can you do?" },
],
});
console.log(response.choices[0].message.content);
External prices and limits come from the linked provider pages and were verified on 2026-09-16. Spotted a change? Tell us.
