6GB VRAM: What You Can Actually Run Locally (2026)
Local AI on a 6GB GPU: GTX 1660, RTX 2060, RTX 3050 and laptop cards. Real weight sizes for chat, coding, vision, speech, translation and RAG.
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Open-Weight LLM Showdown Week 16: Kimi K2.6 Storms the Rankings, Qwen 3.6 Holds the Line, and Consumer GPUs Hit a Ceiling
Three weeks away and the leaderboard reshuffled. Kimi K2.6 brings 1T parameters under open weights, Qwen 3.6 stays the consumer GPU king, and DeepSeek V4-Flash proves too hungry for single-card setups.
Open-Weight LLM Showdown Week 13: DeepSeek V4 Crashes the Party, Gemma 4 Proves Itself, and ICLR Drops Hints
DeepSeek returns with a 1.6T MoE monster under MIT license, Gemma 4's 31B dense model climbs to #3 on Arena AI, and ICLR 2026 papers point to what's next for local inference.
Open-Weight LLM Showdown Week 12: Alibaba's Dense 27B Model Just Made MoE Optional
Qwen3.6-27B scores 77.2% on SWE-Bench Verified with a dense architecture that fits on a single RTX 4090. The MoE efficiency narrative just got complicated.
Open-Weight LLM Showdown Week 11: Qwen 3.6 Fires Back, and the 3B Active War Is Real
Alibaba drops Qwen3.6-35B-A3B with 73.4% on SWE-Bench Verified and Apache 2.0 licensing. The 3-billion active parameter class now has three serious contenders.
Open-Weight LLM Showdown Week 10: NVIDIA Enters the Ring, Meta Walks Out
NVIDIA's Nemotron 3 brings a hybrid Mamba-Transformer architecture to consumer GPUs while Meta abandons open source for proprietary Muse Spark. The open-weight field just reshuffled.
Open-Weight LLM Showdown Week 9: Six Labs, One License, and the Speed War That Decides Everything
Google, Alibaba, Meta, Mistral, OpenAI, and Zhipu all ship competitive open-weight models under permissive licenses. The battleground shifts from benchmarks to inference speed on your actual GPU.
Open-Weight LLM Showdown Week 8: Gemma 4 Rewrites the Rules, Then Trips Over Its Own Feet
Google's Gemma 4 lands with Apache 2.0 licensing and benchmark-topping scores. But a nasty inference speed problem means Qwen still wins on your actual hardware.
Open-Weight LLM Showdown Week 7: Mistral Small 4 Impresses but Stays Out of Reach
Mistral Small 4's 119B MoE unifies reasoning, vision, and coding—but needs datacenter hardware. Qwen 3.5 35B-A3B remains the consumer GPU king at 112 t/s.
Open-Weight LLM Showdown Week 6: MiMo-V2-Flash Brings 309B Parameters to Consumer GPUs
MiMo-V2-Flash runs 309B parameters on RTX 4090s. GLM-5 sets benchmarks but needs datacenters. Llama 4 Scout stays out of reach.
Open-Weight LLM Showdown Week 5: Qwen 3.5 Dominates, Nemotron 3 Super Redefines Efficiency
Qwen 3.5's MoE models hit S-tier benchmarks, NVIDIA's Nemotron 3 Super delivers 5x throughput gains, and GLM-4.7-Flash brings frontier coding to consumer GPUs. The open-weight race just accelerated.
Best Local AI Agent Models: Tool Use by GPU Tier (August 2026)
Which local models can actually use tools, call functions, and run multi-step workflows? Function-calling and TAU-bench picks from 8GB to 32GB VRAM.
Best Local Chat Models by VRAM Tier (August 2026)
Head-to-head comparison of local chat and assistant models from 8GB to 32GB VRAM. Current picks: Qwen3.5, Gemma 4, GPT-OSS, Qwen3.6, and GLM-4.7-Flash.
Best Local Coding Models by VRAM Tier (August 2026)
Which open-weight coding model to run locally? HumanEval and SWE-bench picks from 8GB to 32GB GPUs. Qwen2.5-Coder, Qwen3.6, Devstral, KAT-Coder.
Best Local Models for Translation: Every VRAM Tier (August 2026)
TranslateGemma, NLLB-200, Aya Expanse and Qwen3.5 by VRAM tier, with the licence terms that decide whether you can ship what you run.
Best Local Vision Models: Every GPU Tier (August 2026)
Local image analysis, OCR, and visual reasoning from 8GB to 32GB VRAM. Qwen3.5 replaces Qwen3-VL at most tiers, and 16GB stays unresolved.
12GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on a 12GB GPU: chat, coding, vision, speech and agents for RTX 3060 12GB or RTX 4070. Current picks, per-quant weight sizes, honest limits.
16GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on a 16GB GPU: chat, coding, translation, speech and agents for RTX 4060 Ti, RTX 5060 or Arc A770, and why the vision tier stays unresolved.
24GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on a 24GB GPU: chat, coding, vision, speech and agents for RTX 3090 or RTX 4090. Current picks, per-quant weight sizes, and an open runtime bug.
32GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on a 32GB GPU: chat, coding, vision, speech and agents on an RTX 5090. Current picks, per-quant weight sizes, and what the headroom buys.
8GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on an 8GB GPU: chat, coding, vision, speech and agents for RTX 4060 or RTX 3070. Current picks, named quantisations, honest limits.
Open-Weight LLM Showdown: What Actually Runs on Your GPU in 2026
Forget 700B parameter flagships you can't run. Here are the open-weight models that deliver real performance on consumer hardware - with actual benchmarks.
Qwen3.5-Medium: Frontier AI Performance on a Gaming PC
Alibaba's new 35B model matches Claude Sonnet 4.5 on benchmarks while running locally on an RTX 4090. Here's what you need to know.