DeepSeek V4 vs Kimi K2.5 - China's Trillion-Parameter MoE Duel
Two Chinese open-weight trillion-parameter MoE models with ~32B active parameters each - DeepSeek V4 bets on cost and context, Kimi K2.5 bets on Agent Swarm and verified benchmarks.
Articles Tagged "DeepSeek"
DeepSeek V3.2 vs V4 - What Changes With a Trillion Parameters
A pre-release comparison of DeepSeek V3.2 and V4 - examining the generational leap from 671B text-only to a trillion-parameter natively multimodal model with 1M context.
DeepSeek V4 Drops Next Week - 1 Trillion Parameters on Chinese Chips
DeepSeek will release V4, a natively multimodal trillion-parameter model with a 1M token context window, in the first week of March - optimized for Huawei Ascend chips, not Nvidia.
Huawei Ascend 910B
Huawei Ascend 910B specs, benchmarks, and real-world performance. 64GB HBM2e, ~1,200 GB/s bandwidth, ~600 TFLOPS FP16 - the chip that trained DeepSeek.
DeepSeek Locks Nvidia and AMD Out of V4 - Gives Huawei a Head Start
DeepSeek has denied Nvidia and AMD pre-release access to its upcoming V4 model while granting Huawei and domestic Chinese chipmakers a multi-week optimization window, signaling a strategic pivot toward building a parallel AI software ecosystem on Chinese silicon.
AI Models Can Now Jailbreak Other AI Models Autonomously - 97% Success Rate, No Human Involved
Researchers from Stuttgart and ELLIS Alicante gave four reasoning models a single instruction - 'jailbreak this AI' - and walked away. The models planned their own attacks, adapted in real time, and broke through safety guardrails 97.14% of the time across 9 target models.
DeepSeek V4 Lite Leaks Under NDA - 1M Context, Natively Multimodal, Codenamed Sealion-Lite
DeepSeek's V4 Lite model has leaked through inference provider testing under strict NDAs, revealing a 1M token context window, native multimodal capabilities, and the internal codename sealion-lite.
Kimi K2.5 vs DeepSeek V3.2: The Battle of Open-Weight Chinese MoE Giants
A direct comparison of Kimi K2.5 and DeepSeek V3.2 - two open-weight Chinese MoE models fighting for different corners of the cost-performance frontier.
DeepSeek Trained Its Next Model on Banned Nvidia Blackwell Chips - Washington Wants Answers
A senior Trump administration official confirms DeepSeek trained its upcoming AI model on Nvidia's most advanced Blackwell chips at an Inner Mongolia data center, despite US export controls banning the hardware from reaching China.
DeepSeek V3.2
DeepSeek V3.2 is a 671B-parameter MoE model activating 37B per token that delivers frontier-class reasoning and coding at the lowest API price in the industry - $0.14/$0.28 input, $0.42 output per million tokens.
Qwen3.5-122B-A10B vs DeepSeek V3.2: Efficiency vs Raw Power in Open-Weight AI
A benchmark-by-benchmark comparison of Qwen3.5-122B-A10B and DeepSeek V3.2 - the efficiency-optimized underdog versus the brute-force open-source heavyweight.
Qwen3.5-Flash vs DeepSeek V3.2: Budget API Battle With a Pricing Twist
A detailed comparison of Qwen3.5-Flash and DeepSeek V3.2 API pricing, benchmarks, and tradeoffs - flat-rate simplicity versus cache-dependent discounts in the budget AI tier.
