Best Local Coding Models by VRAM (September 2026)
Open-weight coding LLMs sized by VRAM: Qwen2.5-Coder, Qwen3-Coder, Devstral Small 2, KAT-Coder, GLM-4.7-Flash, and the trade-offs at each tier.
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Open-weight coding LLMs sized by VRAM: Qwen2.5-Coder, Qwen3-Coder, Devstral Small 2, KAT-Coder, GLM-4.7-Flash, and the trade-offs at each tier.
Three AI design tools, one prompt, one task: build a startup landing page. We compare Claude Design, Canva Magic Design, and v0 by Vercel on output quality, speed, and cost.
We compare the three dominant AI coding tools on debugging, refactoring, and feature implementation. SWE-bench scores tell one story — real-world usage tells another.
We tested three top AI image generators on product photos, social media graphics, and text-heavy designs. The results show clear winners for each use case.
We dug into the benchmarks, surveys, and real-world tests to find which AI coding tool actually delivers — not which one has the best marketing.
Five AI tools promise to do your research for you. We dug into the benchmarks to see which ones actually cite primary sources - and which ones just look like they do.
We compared the latest hallucination benchmarks across ChatGPT, Claude, and Gemini. The results are closer than you'd think — and the gaps that matter aren't where you'd expect.
We tested the three leading AI image generators on the same prompts. Here's which one actually wins — and which you can run locally.
We tested the three dominant AI coding tools on real tasks. Here's what each one actually does well, where it falls apart, and what it costs.
We compare seven AI coding agents in March 2026 — from terminal natives to IDE powerhouses. Here's what actually matters for your workflow.
We tested four leading AI image generators on the same product photography task. Here's which one actually delivers.
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.
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.
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.
Local TTS and STT by VRAM tier: Parakeet, Canary, MOSS-Transcribe-Diarize, Step-Audio-EditX, Fish Audio S2 Pro and Kokoro, and the licence each ships.
TranslateGemma, NLLB-200, Aya Expanse and Qwen3.5 by VRAM tier, with the licence terms that decide whether you can ship what you run.
Local image analysis, OCR, and visual reasoning from 8GB to 32GB VRAM. Qwen3.5 replaces Qwen3-VL at most tiers, and 16GB stays unresolved.
We tested four leading AI coding agents on real tasks. Here's what happens when you let them loose on your codebase.
Hands-on testing of Claude, ChatGPT, and Gemini on contract analysis, data extraction, and long document comprehension reveals surprising results
A practical comparison of the five leading AI video generators - costs, generation times, quality, and which one to actually use.
We test the two leading AI image generators head-to-head on photorealism, text rendering, speed, and cost to find which delivers real value in 2026.
Four major AI models launched in 16 days. None of them won. Here's what that means for you.
A head-to-head comparison of the two leading AI code editors in 2026, based on real benchmarks, pricing, and what developers are saying.
The two flagship AI coding models launched the same week. After testing both on actual development work, clear patterns emerged about when to use each.