Kimi K3 leads the current open-weight field for broad capability and agentic work, while GLM-5.3 and DeepSeek V4 offer strong alternatives with different licensing and deployment trade-offs.
Kimi K3 is the strongest all-around pick for frontier capability, long-context work, multimodal input, and agentic coding.
Multiple supplied comparisons identify Kimi K3 as an overall or benchmark leader, with 2.8T total parameters, 104B active, multimodal input, and a 1M-token context.GLM-5.3 is a high-capability long-context choice with a permissive-style MIT predecessor and a newer bespoke license requiring careful review.
Supplied sources repeatedly place the GLM family among the open-weight leaders; GLM-5.3 is reported at 743B total parameters, with a 1M-token context for the family and strong reasoning results.DeepSeek V4 Pro combines frontier-scale reasoning and coding with MIT licensing, but its size makes self-hosting demanding.
Supplied sources describe DeepSeek V4 Pro as a 1.6T-parameter MoE model with 49B active parameters, 1M context, text-only input, and MIT licensing.Qwen3.6 offers the safest broad default for many teams through strong multilingual coverage, a wide size ladder, and Apache 2.0 licensing.
Supplied comparisons call Qwen a leading default local family and describe Qwen3.6 as Apache 2.0, multilingual, and available in dense and MoE sizes.Mistral Small 4 is a practical enterprise-oriented option that combines reasoning, vision, coding, and efficient MoE inference.
Supplied sources report Mistral Small 4 at 119B total parameters with 6.5B active, 128 experts, vision and agentic coding, and Apache 2.0 licensing.Three independent write-ins unlock an honorable mention. The 10 strongest active mentions are shown; inactive mentions archive after 12 months. At 25 recent votes, a contender is scored for possible automatic Top 5 promotion.
No honorable mentions yet. Community suggestions appear below while they gather support.
The five criteria create the AI baseline. The community adjustment is then added or subtracted to produce the current published score.
| Criterion | #1Kimi K3 | #2GLM-5.3 | #3DeepSeek V4 Pro | #4Qwen3.6 | #5Mistral Small 4 |
|---|---|---|---|---|---|
| 95 | 94 | 94 | 88 | 84 | |
| 94 | 93 | 92 | 86 | 86 | |
| 95 | 95 | 95 | 88 | 82 | |
| 96 | 84 | 78 | 86 | 91 | |
| 84 | 89 | 94 | 94 | 93 | |
| AI baseline scoreWeighted criteria result | 93.3 | 91.8 | 91.4 | 88.2 | 86.4 |
| Community adjustmentVote-share influence | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Current published scoreBaseline + community | 93 | 92 | 91 | 88 | 86 |
The five criteria create the AI baseline. The community adjustment is then added or subtracted to produce the current published score.
| Criterion | #1Kimi K3 | #2GLM-5.3 | #3DeepSeek V4 Pro | #4Qwen3.6 | #5Mistral Small 4 |
|---|---|---|---|---|---|
| 95 | 94 | 94 | 88 | 84 | |
| 94 | 93 | 92 | 86 | 86 | |
| 95 | 95 | 95 | 88 | 82 | |
| 96 | 84 | 78 | 86 | 91 | |
| 84 | 89 | 94 | 94 | 93 | |
| AI baseline scoreWeighted criteria result | 93.3 | 91.8 | 91.4 | 88.2 | 86.4 |
| Community adjustmentVote-share influence | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Current published scoreBaseline + community | 93 | 92 | 91 | 88 | 86 |
Choose any two contenders.
We’ll line up what matters.
Moonshot AI
Z.ai
2.8T total; 104B active
743B base; sparse MoE
1,000,000 tokens
1,000,000 tokens
Text, image, and video input
Text-focused open-weight release
Kimi K3 License
GLM-5.3 License
Subjective synthesis of supplied 2026 editorial comparisons, prioritizing recurring capability leaders, coding and agent performance, context, modality, and deployment openness.