AI Model Landscape 2026 — Open Weights, Country Race, and What Actually Runs Locally
Article summary
Quick briefing — cleaned from the original RSS feed
Quick answer: As of July 2026 the open-weight tier splits three ways — Kimi K3 (Moonshot, 2.8T MoE) leads frontend coding, GLM-5.2 (Zhipu, 744B/40B MoE, MIT) tops the open-weights intelligence index and is the value pick, DeepSeek V4 leads raw SWE-bench. For on-device, Qwen3.5-4B and Llama-3.2-3B-Uncensored run on phones. This pillar links the geo/industry spokes. Verify weights shipped before downloading — dates move fast. Educational disclaimer: Model landscape is fast-moving; figures below…
1Key Takeaways
- Quick answer: As of July 2026 the open-weight tier splits three ways — Kimi K3 (Moonshot, 2.8T MoE) leads frontend coding, GLM-5.2 (Zhipu, 744B/40B MoE, MIT) tops the open-weights intelligence index and is the value pick, DeepSeek V4 leads raw SWE-bench.
- For on-device, Qwen3.5-4B and Llama-3.2-3B-Uncensored run on phones.
- This pillar links the geo/industry spokes.
- Verify weights shipped before downloading — dates move fast.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — AI reports that quick answer: As of July 2026 the open-weight tier splits three ways — Kimi K3 (Moonshot, 2.8T MoE) leads frontend coding, GLM-5.2 (Zhipu, 744B/40B MoE, MIT) tops the open-weights intelligence index and is the value pick, DeepSeek V4 leads raw SWE-bench.
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