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
41

Ling 3.0 Flash Fin

InclusionAI
Text & chatVisionLow latency
$0.06 / $0.18262.1K tokensAPI only0.18View
42

Step 3.7 Flash

Stepfun
Text & chatVisionVideo
$0.2 / $1.15262.1K tokensAPI only1.15View
43

GPT-5.6 Luna Pro

OpenAI
Text & chatVisionReasoning
$0.2 / $1.21.05M tokensAPI only1.2View
44

Qwen3.7 Flash

Qwen
Text & chatVisionVideo
$0.03 / $0.131M tokensAPI only0.13View
45

Ling 3.0 Flash Sante

InclusionAI
Text & chatVisionLow latency
$0 / $0262.1K tokensAPI only0View
46

Qwen3.8 Flash

Qwen
Text & chatVisionVideo
$0.15 / $0.471M tokensAPI only0.47View
47

Ling 3.0 Flash

InclusionAI
Text & chatVisionLow latency
$0.021 / $0.063262.1K tokensAPI only0.063View
48

Qwen3.5-Flash

Qwen
Text & chatVisionVideo
$0.065 / $0.261M tokensAPI only0.26View
49

Nemotron 3 Nano Omni

NVIDIA
Text & chatVisionAudio
$0 / $0256K tokensAPI only0View
50

MiniMax M2.5

MiniMax
Text & chatReasoningTool calling
$0.27 / $1.08204.8K tokensAPI only1.08View
51

GLM 4.7 Flash

Z.ai
Text & chatVisionStructured JSON output
$0.0605 / $0.4202.8K tokensAPI only0.4View
52

Nex-N2.5-Mini

Nex Agi
Text & chatLow latencyMultilingual
No public price list262.1K tokensAPI onlyView
53

Seed-2.0-Mini

Bytedance Seed
Text & chatVisionVideo
$0.1 / $0.4262.1K tokensAPI only0.4View
54

Qwen3.6 Flash

Qwen
Text & chatVisionVideo
$0.1875 / $1.1251M tokensAPI only1.125View
55

GLM 5V Turbo

Z.ai
Text & chatVisionVideo
$1.2 / $4202.8K tokensAPI only4View
56

Nano Banana 2 (Gemini 3.1 Flash Image)

Google
VisionAdjustable thinkingImage generation
$0.5 / $3131.1K tokensAPI only3View
57

Qwen3 Coder Flash

Qwen
Text & chatVisionCoding
$0.195 / $0.9751M tokensAPI only0.975View
58

GLM 5 Turbo

Z.ai
Text & chatReasoningTool calling
$1.2 / $4202.8K tokensAPI only4View
59

Seed 1.6 Flash

Bytedance Seed
Text & chatVisionVideo
$0.075 / $0.3262.1K tokensAPI only0.3View
60

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)

Google
VisionAdjustable thinkingImage generation
$0.25 / $1.565.5K tokensAPI only1.5View

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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