Coding · Head-to-head

DeepSeek vs North Mini Code

DeepSeek (freemium, AI Score 8.7/10) vs North Mini Code (free, AI Score 7.8/10). 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 7.8)
  • 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 North Mini Code if…
  • budget is the constraint
  • your primary use case is teams self-hosting a coding agent on their own gpus who need permissive licensing and low memory footprint more than they need frontier-level scores or a million-token window.
Try North Mini Code →

Side-by-side specs

Spec DeepSeek North Mini Code
Category Coding Coding
Pricing model freemium free
Headline pricing Free chat + API from $0.14/M input tokens (V4-Flash beta) Free open weights (Apache 2.0) — you pay only your own compute
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 The weights are unconditionally free under Apache 2.0; your only cost is the compute you run them on. Any hosted-endpoint pricing is set by whoever hosts it, not by the license.
AI Score 8.7/10 7.8/10
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. Teams self-hosting a coding agent on their own GPUs who need permissive licensing and low memory footprint more than they need frontier-level scores or a million-token window.
Editor's pick ✓ Yes
Use cases development agents development agents
Date added 2026-05-01 2026-06-15

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
North Mini Code logo

North Mini Code

Coding · free

Pros

  • Apache 2.0 with no usage restrictions — commercial use, private forks, and immunity from a vendor repricing or retiring the version you run
  • ~3B active parameters means it fits on a single consumer GPU while answering usefully on multi-step repo tasks, a combination still rare
  • Interleaved thinking with native JSON-schema tool calling is purpose-built for agentic loops rather than bolted on afterwards
  • Quantized variants plus vLLM/SGLang/Ollama/Docker support make the local-deployment path genuinely short

Cons

  • ×256K context is now the short end of the open-weights coding tier — GLM-5.2 and MiniMax M3 both ship 1M-token windows
  • ×Near-identical competition: Poolside's Laguna XS.2 is also Apache 2.0, also ~33B/3B MoE, and claims a higher SWE-Bench Verified score from an earlier release
  • ×Benchmark figures (67.6% Verified, 40.2% Pro) are Cohere's own launch claims and have not been independently re-verified here
  • ×Code specialist only, and MoE serving needs vLLM or SGLang — an addition to your stack rather than a replacement, with no confirmed first-party managed hosting
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Updated 2026-08-10. Spec data sourced from official product pages and tracked in our public directory at /tools.