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
21

Gemini 3.1 Flash-Lite

Google
Text & chatVisionAudio
$0.25 / $1.51.05M tokensAPI only1.5View
22

Nano Banana 2

Google
VisionImage generationStructured JSON output
API onlyView
23

Nano Banana 2 Lite

Google
VisionImage generationStructured JSON output
API onlyView
24

Nano Banana Pro

Google
VisionImage generationStructured JSON output
$2 / $12API only12View
25

Gemini Omni Flash

Google
Text & chatVisionAudio
$1.5 / $9API only9View
26

Gemini 3.5 Transcribe

Google
AudioAdjustable thinkingSpeech-to-text
API onlyView
27

Gemini 3.5 Transcribe Live

Google
AudioAdjustable thinkingSpeech-to-text
API onlyView
28

DeepSeek V4 Flash

DeepSeek
Text & chatVisionReasoning
1M tokensAPI onlyView
29

North Mini Code

Cohere
Text & chatCodingLow latency
256K tokensAPI onlyView
30

Jamba2 Mini

AI21 Labs
Text & chatReasoningTool calling
256K tokensAPI onlyView
31

Nova 2 Lite

Amazon
Text & chatVisionVideo
$0.3 / $2.5256K tokensAPI only2.5View
32

Nova Lite

Amazon
Text & chatVisionVideo
300K tokensAPI onlyView
33

Nova Micro

Amazon
Text & chatLow latencyMultilingual
128K tokensAPI onlyView
34

Phi-4 Mini Instruct

Microsoft
Text & chatReasoningTool calling
$0.075 / $0.30131.1K tokensAPI only0.3View
35

Phi-4 Mini Reasoning

Microsoft
Text & chatReasoningTool calling
128K tokensAPI onlyView
36

Qwen3 VL Flash

Alibaba
Text & chatVisionReasoning
$0.05 / $0.4256K tokensAPI only0.4View
37

ERNIE 4.5 Turbo VL

Baidu
Text & chatVisionReasoning
128K tokensAPI onlyView
38

Doubao Seed 2.1 Turbo

ByteDance
Text & chatReasoningTool calling
API onlyView
39

Doubao Seed 2.0 Lite

ByteDance
Text & chatVisionReasoning
API onlyView
40

Doubao Seed 2.0 Mini

ByteDance
Text & chatVisionReasoning
API onlyView

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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