DeepSeek V4 Flash Vision Exp is DeepSeek's experimental vision-enabled take on DeepSeek V4 Flash 0731, released 2026-08, adding image understanding while matching the base model on text tasks. It is a sparse mixture-of-experts model with 13B active parameters out of 284B total, suited to document and chart understanding, visual question answering, and multimodal agent workflows that interleave text and images.
This model isn’t available on MirAPI yet, so the prices shown are the official list prices. Create an account to get notified when it goes live.
Capabilities
Parameters
Request parameters this model accepts through the API.
Benchmarks
bar = score (0–100) · ▏ medianScores come from vendor reports and public leaderboards, not private evals.
Showcase
Every chat model gets the same three fixed prompts. Outputs are archived verbatim, so you can copy a prompt and reproduce the result.
Build a single-file HTML page using three.js from a CDN: a low-poly planet with a tilted ring of ~200 orbiting particles, a soft key light plus rim light, slow auto-rotation, and drag-to-orbit controls. No build tools — one file only.
Every model will run this exact prompt, and its output will appear here verbatim with token counts and the cost per run.
Find the sum of all positive integers n such that n² + 85n + 2017 is a perfect square. Show your reasoning, then give only the final answer on the last line.
Every model will run this exact prompt, and its output will appear here verbatim with token counts and the cost per run.
Extract strict JSON {vendor, invoice_no, issue_date, currency, total, line_items:[{desc, qty, unit_price}]} from the invoice text. Output JSON only.
"Northwind Cloud Ltd. — Invoice NW-20847, issued 12 Mar 2026. 3× GPU-hour bundle at $18.40, 1× object storage 2TB at $9.90. Total $65.10 (USD)."Every model will run this exact prompt, and its output will appear here verbatim with token counts and the cost per run.
Quick start
import os from openai import OpenAI client = OpenAI( base_url="https://api.mirapi.ai/v1", # changed api_key=os.environ["MIRAPI_API_KEY"], # changed ) resp = client.chat.completions.create( model="", messages=[{"role": "user", "content": "Hello"}], )
import OpenAI from "openai"; const client = new OpenAI({ baseURL: "https://api.mirapi.ai/v1", // changed apiKey: process.env.MIRAPI_API_KEY, // changed }); const res = await client.chat.completions.create({ model: "", messages: [{ role: "user", content: "Hello" }], });
curl https://api.mirapi.ai/v1/chat/completions \ -H "Authorization: Bearer $MIRAPI_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "", "messages": [{"role": "user", "content": "Hello"}] }'
# ~/.zshrc export ANTHROPIC_BASE_URL="https://api.mirapi.ai" export ANTHROPIC_AUTH_TOKEN="$MIRAPI_API_KEY" # start as usual (model names stay the same) claude --model
# ~/.codex/config.toml model_provider = "mirapi" model = "" [model_providers.mirapi] name = "MirAPI" base_url = "https://api.mirapi.ai/v1" env_key = "MIRAPI_API_KEY" wire_api = "responses"
Links
1M free tokens to start, no card required. It’s OpenAI-compatible, so you only change the base URL.