GPT-5 nano for fastest llms
GPT-5 nano is the #2 pick on LLMDex's fastest llms ranking out of 5 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
- #2 of 5
- 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 fastest llms on 5 criteria , these are the axes the ranking uses, in priority order:
- Output tokens per second (sustained)
- Time-to-first-token
- Latency consistency under load
- Quality at speed (no garbage tokens to fill time)
- Hosting options that prioritize speed (Groq, Cerebras)
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 can pay slightly more or accept slightly different tradeoffs, Gemini 3 Flash from Google ranks one position higher and tends to win on the hardest cases. 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 fastest llms
- Gemini 3 Flash for fastest llms
Google's high-speed, low-cost mid-tier with the same massive context window, popular for high-volume RAG.
Read guide - Claude Haiku 4 for fastest llms
Anthropic's smallest 4-tier model, fast and cheap with the family's signature tone.
Read guide - GPT-5 mini for fastest 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 - Llama 4 8B for fastest llms
Meta's small Llama 4, built for on-device and edge inference.
Read guide
GPT-5 nano for other use cases
Direct comparisons
Frequently asked
Is GPT-5 nano good for fastest llms?
GPT-5 nano is ranked #2 on LLMDex's fastest 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 fastest llms?
GPT-5 nano costs $0.050 / 1M tokens for input tokens and $0.40 / 1M tokens for output tokens. For fastest llms workloads, output costs typically dominate; budget on the higher number.What's a cheaper alternative to GPT-5 nano for fastest llms?
The next ranked model on this task is Claude Haiku 4. Compare both before committing.When should I NOT use GPT-5 nano for fastest 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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