Fast AI models: 73 low-latency options for chat and autocomplete

Low latency
Services found: 73
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
1

GLM 5.3 Flash

Z.ai
Text & chatVisionVideo
$0.075 / $0.251.31M tokensAPI only0.25View
2

Gemini 3.8 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
3

Gemini 3.7 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
4

GPT-5.6 Luna

OpenAI
Text & chatVisionReasoning
$0.2 / $1.21.05M tokensAPI only1.2View
5

DeepSeek V4 Flash 0731

DeepSeek
Text & chatVisionReasoning
$0.065 / $0.181.31M tokensAPI only0.18View
6

Gemini 3.6 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
7

MiniMax M3

MiniMax
Text & chatVisionVideo
$0.3 / $1.21.05M tokensAPI only1.2View
8

Inkling Small

Thinkingmachines
Text & chatVisionAudio
$0.45 / $1.21.05M tokensAPI only1.2View
9

DeepSeek V4 Flash 0423

DeepSeek
Text & chatVisionReasoning
$0.088606 / $0.1772121.05M tokensAPI only0.177View
10

GPT-5.4 Mini

OpenAI
Text & chatVisionReasoning
$0.75 / $4.5400K tokensAPI only4.5View
11

MiniMax M2.7

MiniMax
Text & chatReasoningTool calling
$0.3 / $1.2204.8K tokensAPI only1.2View
12

Gemini 3.5 Flash-Lite

Google
Text & chatVisionAudio
$0.3 / $2.51.05M tokensAPI only2.5View
13

GPT-5.4 Nano

OpenAI
Text & chatVisionReasoning
$0.2 / $1.25400K tokensAPI only1.25View
14

Claude Haiku 4.5

Anthropic
Text & chatVisionReasoning
$1 / $5200K tokensAPI only5View
15

Mistral Small 4

Mistral AI
Text & chatVisionReasoning
$0.15 / $0.6256K tokensAPI only0.6View
16

Nemotron 3 Nano 30B A3B

NVIDIA
Text & chatReasoningTool calling
$0.05 / $0.2262.1K tokensAPI only0.2View
17

Ministral 3 14B 2512

Mistral AI
Text & chatVisionReasoning
$0.2 / $0.2262.1K tokensAPI only0.2View
18

Ministral 3 8B 2512

Mistral AI
Text & chatVisionReasoning
$0.15 / $0.15262.1K tokensAPI only0.15View
19

Ministral 3 3B 2512

Mistral AI
Text & chatVisionReasoning
$0.1 / $0.1131.1K tokensAPI only0.1View
20

GPT-Realtime-2.1 Mini

OpenAI
Text & chatVisionAudio
$0.6 / $2.4128K tokensAPI only2.4View

Browse by need

These 73 models are the small, fast members of each family - Flash, Mini, Lite, Nano and Haiku variants - built for workloads where response time and request volume matter more than depth. Output runs from $0.10 to $5 per million tokens, an order of magnitude below the frontier.

Typical uses: routing and classification, autocomplete, moderation passes, first-line support. GLM 5.3 Flash, Gemini 3.8 Flash and Gemini 3.7 Flash head the list. These models are weaker at long multi-step reasoning, so the common pattern is a fast model in front, escalating to a frontier model only when the task warrants it.

Small by designThese are the Flash, Mini, Lite and Haiku variants, not throttled versions of big models.
Cheap enough to overuseAt $0.10 per 1M tokens you can afford a model call where you used to write a rule.
Escalate, do not compromisePair with a frontier model for the cases the fast one cannot close.

Models with this capability

How to choose

  • Measure time to first token, not just total time — perceived speed lives there.
  • Test on your hardest realistic input; small models degrade suddenly rather than gradually.
  • Check context limits, which are often smaller on the fast variants.
  • Design the escalation rule before launch, not after the first complaint.

Common mistakes

Using a fast model for long reasoningIt will answer quickly and be wrong quickly.
No escalation pathEvery product has a tail of requests a small model cannot handle.

Who this suits

Real-time interfacesAutocomplete, inline suggestions, live moderation.
High-volume classificationMillions of routing decisions where each one is simple.
Cost-constrained productsFree tiers and low-ARPU features that still need model calls.

Frequently asked questions

What do I give up for speed?

Depth on long multi-step reasoning and reliability in extended tool chains. For routing, classification and autocomplete you give up nothing that matters.

What is the common architecture?

A fast model in front, escalating to a frontier model only when confidence is low or the task is complex.

Which are the cheapest?

GLM 5.3 Flash, Gemini 3.8 Flash and Gemini 3.7 Flash, with output from $0.10 per 1M tokens.

How much faster are they really?

Typically several times, and the gap widens on short answers.

Do they support tools and JSON?

Most do, though reliability on long tool chains is lower.

Frequently searched

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