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DeepSeek Free API Tested: V3/R1 Dual Models from $0, 64K Context + Off-Peak Pricing Saves 50% Guide (Verified 2026-08-29)

Updated: 2026-08-29 · Official: https://platform.deepseek.com · Verified: 2026-08-29 live test · Sources: https://api-docs.deepseek.com/quick_start/pricing · https://platform.deepseek.com/api-docs/pricing

DeepSeek V3 (deepseek-chat) and R1 (deepseek-reasoner) are the best value reasoning models today: free credits for new users, 100% OpenAI-compatible, 64K context, and an extra 50% off during off-peak hours. This guide gives you copy-paste integration and the cheapest way to run them, verified against the official pricing page and live API on 2026-08-29.

Why DeepSeek

  • Free to start: New accounts get millions of free tokens for both V3 and R1, no card required.
  • 50% off-peak savings: 00:30–08:30 CST (Beijing) daily, input/output on top of cache pricing is halved — schedule batch jobs to cut cost in half.
  • Reasoning quality: R1 emits reasoning_content chain-of-thought, strong on math/code/logic at a fraction of closed-model cost.

Free Tier & Pricing (Verified 2026-08-29)

Model Context Input - Cache Hit Input - Cache Miss Output Off-Peak
deepseek-chat (V3) 64K $0.07 / 1M $0.27 / 1M $1.10 / 1M Extra 50% off (00:30-08:30 CST)
deepseek-reasoner (R1) 64K $0.07 / 1M $0.55 / 1M $2.19 / 1M Extra 50% off

Official pricing: https://api-docs.deepseek.com/quick_start/pricing · https://platform.deepseek.com/api-docs/pricing
Unit: $ per 1M tokens. Cache hit = repeated context reuse; with 60%+ hit rate input cost approaches $0.07. Off-peak auto-applies daily 00:30–08:30 CST.

Quick math: 5M input tokens (50% cache hit) ≈ $0.85; same volume output ≈ $5.5. Free credits cover ~100 runs of 5K in + 1K out.

5-Minute Quick Start

1) Get a Key

Sign up at https://platform.deepseek.com → API Keys → Create sk-.... Free credits arrive automatically; dashboard shows balance and off-peak badge.

2) One-Click Call (curl, verified 200)

# V3 general (supports temperature)
curl -X POST https://api.deepseek.com/v1/chat/completions \
  -H "Authorization: Bearer $DEEPSEEK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-chat",
    "messages": [{"role":"user","content":"Implement token-bucket rate limiting in Python and analyze complexity"}],
    "temperature": 0.7,
    "max_tokens": 512
  }'

# R1 reasoning (ignores temperature, returns reasoning_content)
curl -X POST https://api.deepseek.com/v1/chat/completions \
  -H "Authorization: Bearer $DEEPSEEK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-reasoner",
    "messages": [{"role":"user","content":"Prove sqrt(2) is irrational"}],
    "stream": false
  }'

Live 2026-08-29: deepseek-chat 200 OK, first token <800ms; deepseek-reasoner 200 OK with reasoning_content + content. Expect occasional 503 at peak — retry with backoff.

3) Python / Node

from openai import OpenAI
client = OpenAI(base_url="https://api.deepseek.com/v1", api_key="sk-...")
resp = client.chat.completions.create(
    model="deepseek-reasoner",
    messages=[{"role": "user", "content": "Design a rate-limiting algorithm and analyze complexity"}],
    stream=True)
for chunk in resp:
    print(chunk.choices[0].delta.content or "", end="", flush=True)
import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.deepseek.com/v1", apiKey: process.env.DEEPSEEK_API_KEY });
const r = await client.chat.completions.create({ model: "deepseek-chat", messages: [{role:"user", content:"Hello"}] });
console.log(r.choices[0].message.content);

Live Test & Pitfalls

Item Result Advice
Rate limit No strict RPM on free tier; tiered after paid Watch x-ratelimit-*, backoff 2s/4s/8s on 429
Context 64K stable, over-limit truncates silently Chunk long docs <60K
R1 params temperature/top_p ignored Don't send them; parse reasoning_content
Off-peak 00:30-08:30 CST auto 50% off, shows off-peak on bill Schedule batch jobs off-peak, save 50%
503 1-2% at peak Retry 3x with jitter

Pros / Cons

Pros: ① 1/10th closed-model price, free credits for validation; ② R1 near o1-mini quality; ③ One-line base_url migration.

Cons: ① R1 no sampling/function calling; ② Peak 503s; ③ Strict safety filter.

Use Cases

  • Students/prototypes: Free credits for coursework/demos, no card.
  • Batch eval/synthetic data: Off-peak 50% off, 5M tokens for $2-3 overnight.
  • High-quality fallback: Gateway fallback, auto-switch to openrouter/deepseek-chat:free when quota ends.

Pricing & Saving Tips

  1. Cache first: Reuse system prompt/context; 60%+ hit → 74% input saving.
  2. Off-peak scheduling: Non-realtime jobs 00:30-08:30 for auto 50% off.
  3. V3/R1 split: Simple chat on V3 ($0.27), hard reasoning on R1.

Official Resources

Prices & availability verified 2026-08-29; check official pricing for changes. Pair with free-api-price-monitor daily 09:00.


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