Inference APIs
Compare/Chat

DeepSeek V4.1 Flash vs GPT-OSS 120B

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 V4.1 FlashGPT-OSS 120B
ProviderDeepSeekOpenAI
Model iddeepseek-ai/DeepSeek-V4.1-Flashopenai/gpt-oss-120b
Input price$0.40 / 1M tokens$0.20 / 1M tokens
Output price$1.60 / 1M tokens$0.80 / 1M tokens
Context window1M tokens131K tokens
CapabilitiesChat, Reasoning, Tool calling, JSON mode, 1M contextChat, Reasoning, Tool calling, JSON mode, 131K context
WeightsOpenOpen
AvailabilityAvailable on Inference APIsAvailable on Inference APIs
Rate limitsNo daily caps; pay per requestNo daily caps; pay per request
Time to first token0.41 s0.93 s
Output speed388.7 tokens / s132.9 tokens / s

Cost for 1M input + 1M output tokens

DeepSeek V4.1 Flash
$2
GPT-OSS 120B
$1

GPT-OSS 120B 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 V4.1 Flash — The newest DeepSeek Flash model: better reasoning and tool use than V4 Flash, still with a 1M-token context.
  • GPT-OSS 120B — OpenAI's open-weight 120B reasoning model. Strong at coding, tool use and agentic tasks; the drop-in replacement Groq recommends for Llama 3.3 70B.

Try DeepSeek V4.1 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-V4.1-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-V4.1-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-V4.1-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.