11 articles
DeepSeek V4 Pro lands a 63.5 on SWE-bench Verified at $0.435/$0.87 per million tokens, and Flash runs agent inner loops for cents. Here is the worked cost math, the Flash-vs-Pro split, and a clear guide on when to route to DeepSeek instead of a frontier model.
A data-rich, source-cited comparison of the three open-weights coding models that matter in 2026: GLM-5.2, DeepSeek V4, and Qwen3. Benchmark table, per-token pricing, context windows, self-host footprint, and a clear pick-X-if decision matrix.
deepseek-chat is deprecated and disappears July 24, 2026 - here is how to migrate to V4 Flash or Pro, with verified pricing, thinking-mode mapping, and a step-by-step checklist.
GPT-5.4 vs Gemini 3.1 Pro vs DeepSeek V4: pricing, benchmarks, context behavior, and license terms for the mid-tier models that carry most production traffic.
DeepSeek V4-Flash costs $0.28 per million output tokens. Fable 5 costs $50. That 178x gap is real - but so is the quality difference. Here is where it matters and where it does not.
A first-hand visit to DeepSeek HQ reveals something more interesting than benchmark scores: a 300-person company that treats AI as infrastructure, not eschatology - and what that means for API pricing everywhere.
Reasonix hit Hacker News with a DeepSeek-native pitch: keep long coding sessions cheap by designing the agent loop around prefix caching. The interesting question is when cache efficiency helps quality, and when it fights the harness.
DeepSeek V4 is trending because it is close enough to frontier coding models at a much lower token price. The real question for developers is where cheap reasoning belongs in an agent stack.
DeepSeek V4 splits into Flash and Pro, ships a 1M context window, and undercuts every closed model on price. Here's how to wire it up with the OpenAI SDK, when to pick it over Claude or GPT, and what changed since V3 and R1.
GRPO is suddenly the standard RL recipe for reasoning models. A no-prior-knowledge mental model of PPO, GRPO, and how DeepSeek R1's training works under the hood.
DeepSeek's R1 and V3 models deliver frontier-level performance under an MIT license. Here's how to use them through the API, run them locally with Ollama, and decide when they beat closed-source alternatives.
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