Coding · Head-to-head

DeepSeek vs MiniMax M3

DeepSeek (freemium, AI Score 8.7/10) vs MiniMax M3 (freemium, AI Score 8.2/10). Side-by-side pricing, features, pros and cons, and which to pick.

The verdict

Pick DeepSeek if…
  • overall capability matters more than price (AI Score 8.7 vs 8.2)
  • you want our editor's pick for this category
  • your primary use case is developers who own their agent harness and can hold a stable prompt prefix, since the cache rate is what makes deepseek cheap, and whose work is text rather than screenshots or audio.
Try DeepSeek →
Pick MiniMax M3 if…
  • your primary use case is backend and agent developers running high-token coding workloads who need frontier-adjacent output at open-weights prices, plus teams that must self-host the model to keep source code on their own infrastructure.
Try MiniMax M3 →

Side-by-side specs

Spec DeepSeek MiniMax M3
Category Coding Coding
Pricing model freemium freemium
Headline pricing Free chat + API from $0.14/M input tokens (V4-Flash beta) Freemium — open weights + usage-based API ($0.30/$1.20 per M at launch; check site for current)
Free tier Free web and mobile chat with daily usage limits; API is pay-as-you-go, check the platform console for any current credit offer A free API tier for evaluation was available at launch, plus free self-hosting via the open weights. Check platform.minimax.io for current limits.
AI Score 8.7/10 8.2/10
Best for Developers who own their agent harness and can hold a stable prompt prefix, since the cache rate is what makes DeepSeek cheap, and whose work is text rather than screenshots or audio. Backend and agent developers running high-token coding workloads who need frontier-adjacent output at open-weights prices, plus teams that must self-host the model to keep source code on their own infrastructure.
Editor's pick ✓ Yes
Use cases development agents development agents
Date added 2026-05-01 2026-06-09

Pros and cons

DeepSeek logo

DeepSeek

Coding · freemium

Pros

  • V4-Flash lists $0.14/M input and $0.28/M output, roughly 36x and 107x under GPT-5.6 Sol's $5 and $30
  • Cache hits at $0.003/M make a repeated agent prefix nearly free, blending to about $0.06/M on an agent-shaped traffic mix
  • MIT-licensed 284B/13B-active weights on Hugging Face, so the same model can be self-hosted or fine-tuned
  • 1M-token context on both V4-Pro and V4-Flash handles whole codebases without chunking
  • Native Responses API plus stated Codex adaptation lets agent harnesses point at it without a chat shim

Cons

  • ×Text in, text out — no image, audio or video input, so screenshot-driven debugging is off the table
  • ×V4-Flash is a public beta: no SLA, movable rate limits, and no published throughput figure (Artificial Analysis lists Speed as N/A)
  • ×Verbose output — 210M tokens across nine evaluations against a 100M median, which eats into the cheap-token advantage
  • ×China-hosted inference, and the Responses path parks conversation state on DeepSeek's servers, a compliance question before an engineering one
MiniMax M3 logo

MiniMax M3

Coding · freemium

Pros

  • Launch API pricing of $0.30/$1.20 per M tokens runs roughly an order of magnitude under GPT-5.6 Sol's $5/$30, and undercuts even OpenAI's cheap Luna tier
  • Open weights allow self-hosting, fine-tuning on proprietary code, and full inspection — no revocable API terms
  • 1M-token context ingests an entire codebase or a long agent history without chunking
  • Served through OpenRouter and other third-party hosts, so evaluation does not require onboarding to MiniMax's platform
  • Tuned specifically for multi-step tool use rather than single-turn completion, which is what agent frameworks actually need

Cons

  • ×The open-weights coding niche closed around it: GLM-5.2 ships 744B parameters under a permissive MIT license and Kimi K3 matches the 1M context, so nothing in M3's spec sheet is unique anymore
  • ×MiniMax called the launch API rate promotional and has not committed to a durable published price — budget with the pricing page open rather than from a cached figure
  • ×Text and image in, text out only. No voice mode, no computer use, no video generation; those live in separate MiniMax models you call separately
  • ×Developer tooling and native IDE integration remain thinner than OpenAI's or Anthropic's, and Chinese-lab origin still stalls procurement at some enterprises
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Updated 2026-08-10. Spec data sourced from official product pages and tracked in our public directory at /tools.