GPT-5 nano for cheapest llms
GPT-5 nano is the #1 pick on LLMDex's cheapest llms ranking out of 6 models we track for this use case. Below, the specific reasons it slots where it does, and when you should reach for an alternative.
Updated
At a glance
- Rank
- #1 of 6
- Context
- 400K tokens
- Output / 1M
- $0.40 / 1M tokens
- Released
- Aug 2025
Why GPT-5 nano fits this task
Three things about GPT-5 nano that map directly onto what this task rewards: Fast P99 latency. Beyond the task-specific fit, GPT-5 nano also brings lowest-cost openai model with vision support and good enough for routing and classification, both of which compound when the workload broadens.
The criteria this task rewards
LLMDex ranks cheapest llms on 5 criteria , these are the axes the ranking uses, in priority order:
- Output price per 1M tokens
- Quality floor, must clear basic instruction-following
- Latency
- Context window adequacy (≥32k)
- API stability and rate-limit headroom
How GPT-5 nano scores on each axis
Where GPT-5 nano costs you: visible quality gap on open-ended tasks. For most teams this is acceptable on this workload, the value of the strengths above outweighs the cost. For cost-bound workloads or teams with strict latency budgets, run an eval against the next two ranked models on real data before committing.
Strengths that pay off here
- Lowest-cost OpenAI model with vision support
- Fast P99 latency
- Good enough for routing and classification
Tracked weaknesses
- Visible quality gap on open-ended tasks
- Limited reasoning capability
When to pick something else
If you have a binding constraint that GPT-5 nano doesn't satisfy, pricing, license, regional availability, modality coverage, the next-best pick on this task is Gemini 3 Flash from Google. Google's high-speed, low-cost mid-tier with the same massive context window, popular for high-volume RAG.
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Other models for cheapest llms
- Gemini 3 Flash for cheapest llms
Google's high-speed, low-cost mid-tier with the same massive context window, popular for high-volume RAG.
Read guide - GPT-5 mini for cheapest llms
GPT-5's mid-tier sibling, most of the quality at a fraction of the price, ideal for high-volume production workloads.
Read guide - Claude Haiku 4 for cheapest llms
Anthropic's smallest 4-tier model, fast and cheap with the family's signature tone.
Read guide - DeepSeek-V3 for cheapest llms
DeepSeek's flagship 671B-parameter MoE, frontier-level quality at a tiny fraction of frontier prices.
Read guide - Qwen2.5-72B for cheapest llms
The previous-generation Qwen flagship, still widely deployed for stability.
Read guide
GPT-5 nano for other use cases
Direct comparisons
Frequently asked
Is GPT-5 nano good for cheapest llms?
GPT-5 nano is ranked #1 on LLMDex's cheapest llms list. OpenAI's smallest GPT-5 variant, built for ultra-low-cost classification, routing, and high-volume inference.How much does GPT-5 nano cost for cheapest llms?
GPT-5 nano costs $0.050 / 1M tokens for input tokens and $0.40 / 1M tokens for output tokens. For cheapest llms workloads, output costs typically dominate; budget on the higher number.What's a cheaper alternative to GPT-5 nano for cheapest llms?
The next ranked model on this task is Gemini 3 Flash. Compare both before committing.When should I NOT use GPT-5 nano for cheapest llms?
Tracked weakness: Visible quality gap on open-ended tasks. If that constraint is binding for your workload, the next-ranked model on this task is the safer pick.
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