Fetching from the wire…
01
02
03
04
05
06
07
08
Top 5 · 2026-04-26 · source-backed
DeepSeek released V4 on April 24 and the numbers demand attention. V4-Pro is 1.6 trillion parameters total with 49 billion active, MIT-licensed, native 1M-token context. It scores 80.6% on SWE-bench Verified, putting it within 0.2 points of Claude Opus 4.6. On Terminal-Bench 2.0 it actually leads Claude: 67.9% vs 65.4%. LiveCodeBench: 93.5% vs 88.8%.
V4-Flash is the more interesting play for production use. 284B total parameters, 13B active, priced at $0.14/$0.28 per million tokens. That's the cheapest model in its performance tier by a wide margin. LMSYS benchmarked throughput at 199 tokens/sec on B200 and 266 tokens/sec on H200, with throughput dropping only 10% from 4K to 900K context tokens. That's a remarkably flat scaling curve.
The architecture is genuinely novel. Hybrid Attention combining Compressed Sparse Attention and Heavily Compressed Attention cuts inference FLOPs to 27% and KV cache to 10% compared to V3.2 at 1M context. Community analysis on r/LocalLLaMA shows KV cache dropping from 83.9 GiB to 9.62 GiB at 1M tokens. That's a 10x reduction, and it's what makes the pricing possible.
Then there's the chip story. Fortune reports Huawei confirmed V4 runs on Ascend 950 supernodes. First trillion-parameter MoE deployed without any NVIDIA hardware. DeepSeek rewrote their stack from CUDA to Huawei's CANN framework, with Cambricon and Moore Threads chips also supported. US export controls were supposed to prevent exactly this. They didn't.
What should you do? If you're running any batch processing, RAG pipelines, or high-volume agent workflows, V4-Flash deserves a serious evaluation this week. At $0.14/M input tokens versus $3/M for Claude Sonnet or $15/M for Opus, the cost difference funds a lot of quality-checking infrastructure. I'm not saying it replaces Opus for complex reasoning. I'm saying for 70% of the token volume in most production systems, it might be good enough at 1/100th the price. That's worth testing.
Each link below shares sources, entities, or timing with this story.
DeepSeek partners with Huawei / Shared entities / Same source / Shared topic / Earlier coverage
Linked by a graph relationship (DeepSeek partners with Huawei); both cover April, Bench, Community, DeepSeek; cite the same source (V4-Pro).
Ollama supports DeepSeek / Shared entities / Same source domain / Shared topic / Earlier coverage / Tension
Linked by a graph relationship (Ollama supports DeepSeek); both cover April, Claude Opus, LocalLLaMA, MoE; reported by the same outlet (reddit.com, simonwillison.net).
Ollama supports DeepSeek / Shared entities / Same source domain / Shared topic / What happened next
Linked by a graph relationship (Ollama supports DeepSeek); both cover April, Bench, CUDA, DeepSeek; reported by the same outlet (reddit.com).
Unsloth Studio supports DeepSeek / Shared entities / Same source domain / Shared topic / What happened next
Linked by a graph relationship (Unsloth Studio supports DeepSeek); both cover Claude Opus, CUDA, DeepSeek, Flash; reported by the same outlet (reddit.com).
DeepSeek released DeepSeek V4 / Shared entities / Same source domain / Shared topic / Earlier coverage / Tension
Linked by a graph relationship (DeepSeek released DeepSeek V4); both cover April, Bench, Claude Opus, Flash; reported by the same outlet (simonwillison.net).
DeepSeek competes with Anthropic / Shared entities / Shared topic / What happened next
Linked by a graph relationship (DeepSeek competes with Anthropic); both cover Bench, CLAUDE, Claude Opus, DeepSeek; overlapping topics (claude, deepseek, model).
Linked by a graph relationship (DeepSeek competes with Anthropic); both cover April, Claude Opus, DeepSeek, LocalLLaMA; overlapping topics (context, cost, model, parameter, token).
DeepSeek competes with Anthropic / Shared entities / Shared topic / Earlier coverage / Tension
Linked by a graph relationship (DeepSeek competes with Anthropic); both cover Claude Opus, DeepSeek, MIT, MoE; overlapping topics (active, model, opus, parameter).