GPT-6 Luna vs GLM 5.3 Flash vs DeepSeek V4.1 Flash: The Budget Speed Tier

The efficient tier keeps getting better. GPT-6 Luna after its 80% price cut, GLM 5.3 Flash, and DeepSeek V4.1 Flash now overlap on enough use cases that picking wrong costs real money at volume. This is a routing guide, not a ranking.

Pricing and Specs

GPT-6 Luna: $0.20/$1.20 per million tokens, 1.05M context, full OpenAI tool suite (hosted shell, computer use, MCP, web search) and reasoning-effort controls. GLM 5.3 Flash: Zhipu's speed-optimized tier, strong coding scores for its price class, available on Baseten and via Multos. DeepSeek V4.1 Flash: $0.14/$0.28, 1M context, MIT license, ~127 tok/s — the throughput floor for frontier-capable AI.

Where Each Model Wins

Use GPT-6 Luna when the task needs OpenAI tooling — hosted shell, apply patch, computer use — or benefits from reasoning-effort tuning; its 92.3% GPQA Diamond leads this trio on professional reasoning. Use GLM 5.3 Flash when you want strong coding performance at flash-tier pricing; it is the balanced default of the three. Use DeepSeek V4.1 Flash when raw throughput and cost dominate: classification, extraction, routing, structured pipelines at millions of tokens per day.

The One-Line Routing Rule

V4.1 Flash for volume. GLM 5.3 Flash for balanced coding on a budget. GPT-6 Luna for tool-heavy or reasoning-heavy tasks. Auto mode on Multos routes across all three already — manual selection is for when you know the task type upfront.

Effective Cost at Production Cache Rates

At 85% cache hit rate and 95:5 input/output ratio: DeepSeek V4.1 Flash blends near ~$0.05/M, GPT-6 Luna near ~$0.11/M. For a 70M-token month the gap is real but narrow — quality and task fit should drive the decision before price.

Ready to Get Started?

All three models are live on Multos Lite and above. Pick from the model dropdown or let Auto Router decide.

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