7d • AI
DeepSeek V4 Dropped
China just dropped DeepSeek V4 this morning. And the pricing is borderline offensive to OpenAI.
Two models launched. Both open source.
DeepSeek V4 Pro: 1.6 trillion parameters (49B active). The big one. Built for complex reasoning, coding, and agentic workflows.
DeepSeek V4 Flash: 284 billion parameters (13B active). The fast one. Almost identical performance on most tasks, fraction of the cost.
Both support a 1 million token context window. That's not a typo. One million.
The pricing that matters:
Flash: $0.14 per million input tokens, $0.28 outputPro: $1.74 input, $3.48 output
Compare that to GPT-5.5 at $5/$30 per million. Or Claude at $5/$25.
DeepSeek V4 Pro costs 7x less than Claude for nearly identical performance on coding benchmarks.
Flash costs even less and runs faster.
Performance reality check:
DeepSeek admits they're 3 to 6 months behind GPT-5.4 and Gemini 3.1 Pro on reasoning benchmarks.
But on coding? They're competitive. Sometimes better.
SWE-bench Verified: 80.6% (Claude is 80.8%)LiveCodeBench: 93.5% (beats Claude's 88.8%)Codeforces rating: 3206 (competitive with GPT-5.5)
For anyone building tools, automating workflows, or generating code, the gap doesn't matter. The price does.
Three features that hit different for wired brains:
1. Million-token context = brain dump friendly
You don't have to organize your thoughts before you paste them in. Entire project folders. Messy notes. All of it. One prompt. Your brain doesn't think in neat outlines. Now your AI doesn't require them either.
2. Three reasoning modes
Non-thinking: Fast responses. Good for quick iteration.Think High: Mid-level reasoning. Balanced.Think Max: Deep reasoning chains. Solves complex problems but burns more tokens.
You pick based on the task. Not locked into one speed.
3. Open source under MIT license
You can download it. Run it locally. Fine-tune it. Customize it for how you actually work.
No black box. No rate limits. No sudden policy changes that break your workflow.
If you've got the hardware (this is not a laptop model), you own it.
Tips if you're testing it:
Start with Flash. It's cheaper and faster. Only move to Pro if you hit a wall on complex tasks.
Use the cache-hit discount. If you're running multiple queries with the same system prompt, the first call is full price. Every repeat is 80 to 92% off. Structure your workflows around repeated prefixes.
Set temperature=1.0 and top_p=1.0. DeepSeek tuned the model with these settings. Don't import your GPT defaults.
Watch your output token limits. The 1M context is for input. Most answers fit in 2K output tokens. Don't expect 50K responses.
Test it on your actual workload. Not synthetic benchmarks. Take a task you currently send to GPT-4 or Claude. Run it through V4 Flash. If quality is close and cost is 10x lower, you found a use case.
Access:
Both models went live today.
Why this matters for MindX:
AI is the cognitive infrastructure that catches what your brain drops.
But if every test costs $30, you stop experimenting. You second-guess. You ration usage.
DeepSeek makes it cheap enough to burn tokens without guilt. To iterate. To fail fast. To build the exact tool your brain needs without asking permission or watching a budget.
That's the unlock.
Not the benchmarks. The freedom to build wrong 100 times until you build it right.
Drop a comment: What's the first thing you'd build or automate if AI cost was no longer a barrier?
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DeepSeek V4 Dropped
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