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NaiveAI Promises 2,100 Tokens per Second. How Well Does It Code?
NaiveAI承诺每秒2,100个token。它的编程能力如何？
Developers weighing NaiveAI's claimed 2,100 tokens per second should note that speed may tempt teams to accept weaker code quality than DeepSeek delivers.
Judgment
Developers choosing a coding model for latency-sensitive iteration should treat Naive-N0.5-Flash as a speed-first option, but its higher cost per question and longer hard-problem reasoning mean teams must decide whether median 3.1s responses justify that tradeoff.
Basis
Latent Space's hands-on test says Naive-N0.5-Flash approaches or passes 1,000 tokens per second in both thinking configurations, with a median end-to-end response of 3.1s versus 5.3s for GLM 5.3 Flash (high) and 10.1s for DeepSeek V4.1 Flash 1017 (high), and it suggests coding quality holds up against DeepSeek. The tradeoff is in the same test: Naive takes longer on hard problems, 89.8s versus 79.7s, and carries a slightly higher cost per question. Mechanically, NaiveAI continued MiMo-V2.5 — a 310B-parameter sparse MoE with 15B active parameters — with roughly 3.25T additional tokens, about 3T at 1M context, then paired it with its NaiveRT engine.
- Naive-N0.5-Flash (thinking)3.1 s
- GLM 5.3 Flash (high)5.3 s
- DeepSeek V4.1 Flash 1017 (high)10.1 s
Unclear The source does not say whether Naive-N0.5-Flash's faster median responses remain correct, because it did not grade answer accuracy and used only 10 questions per difficulty level.
Next Watch for Artificial Analysis to publish NaiveAI speed and intelligence scores, and for a larger graded coding evaluation to test whether the quality claim holds.