Text and chat AI models: the 228 that write and converse

Text & chat
Services found: 228
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
21

GLM 5.3 Flash

Z.ai
Text & chatVisionVideo
$0.075 / $0.251.31M tokensAPI only0.25View
22

Gemini 3.8 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
23

Qwen3.8 Max (0902)

Qwen
Text & chatVisionVideo
$2 / $61M tokensAPI only6View
24

Qwen3.8 2.4T A95B

Qwen
Text & chatReasoningAdjustable thinking
$2 / $61.05M tokensAPI only6View
25

Muse Spark 1.2

Meta
Text & chatVisionAudio
$1.25 / $4.251.05M tokensAPI only4.25View
26

Gemini 3.7 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
27

Grok 4.5

xAI
Text & chatVisionReasoning
$2 / $6500K tokensAPI only6View
28

GPT-5.5

OpenAI
Text & chatVisionReasoning
$5 / $301.05M tokensAPI only30View
29

Claude Sonnet 5

Anthropic
Text & chatVisionReasoning
$2 / $101M tokensAPI only10View
30

GPT-5.6 Luna

OpenAI
Text & chatVisionReasoning
$0.2 / $1.21.05M tokensAPI only1.2View
31

DeepSeek V4 Pro 0813

DeepSeek
Text & chatReasoningAdjustable thinking
$1.0494 / $3.14821.05M tokensAPI only3.148View
32

DeepSeek V4 Flash 0731

DeepSeek
Text & chatVisionReasoning
$0.065 / $0.181.31M tokensAPI only0.18View
33

Gemini 3.6 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
34

Muse Spark 1.1

Meta
Text & chatVisionAudio
$1.25 / $4.251.05M tokensAPI only4.25View
35

Qwen3.8 27B

Qwen
Text & chatVisionVideo
$0.42 / $31M tokensAPI only3View
36

DeepSeek V4 Pro 0423

DeepSeek
Text & chatReasoningAdjustable thinking
$0.95526 / $1.910521.05M tokensAPI only1.911View
37

Claude Sonnet 4.6

Anthropic
Text & chatVisionReasoning
$3 / $151M tokensAPI only15View
38

Qwen3.7 Max

Qwen
Text & chatReasoningAdjustable thinking
$2.5 / $7.51M tokensAPI only7.5View
39

MiniMax M3

MiniMax
Text & chatVisionVideo
$0.3 / $1.21.05M tokensAPI only1.2View
40

GLM-5.1

Z.ai
Text & chatReasoningTool calling
$1.4 / $4.4200K tokensAPI only4.4View

Browse by need

Text generation is the baseline every language model shares, which is why 228 of the 239 models in this rating qualify - and why price, not capability, is usually what decides. Output rates span two orders of magnitude: $0.25 per million tokens at the budget end, $50 at the frontier with Claude Fable 5.1 and GPT-6 Astra.

For ordinary writing, summarising and conversation, the mid tier is where the value sits. Claude Sonnet 5 at $10 and GPT-5.6 Terra at $12 handle most professional work, and Gemini 3.8 Flash does it for $3.75 while promotional pricing lasts. Reserve the frontier models for work where a wrong answer is expensive.

Output is the billAnswers cost three to five times what prompts do, so length discipline beats model shopping.
Mid tier is the sweet spotSonnet 5 and GPT-5.6 Terra deliver most frontier quality at a fifth of the price.
Context is not freePasting long documents into every request is the most common source of surprise invoices.

Models with this capability

How to choose

  • Decide whether you need reasoning at all — plain chat models answer faster and cheaper.
  • Match the context window to your longest realistic input, not to the largest number on offer.
  • Check whether the vendor offers batch and caching; both change the economics more than the headline rate.
  • If you serve non-English users, test tokenisation cost on real text before committing.

Common mistakes

Paying frontier rates for routine repliesA support bot answering FAQs does not need a $50 model. Route by complexity instead.
Ignoring the free tiersGoogle, DeepSeek, Qwen and Mistral all let you validate quality before spending anything.

Who this suits

Product teamsStart on the mid tier, measure, then move up or down per feature.
High-volume operationsBudget models plus batch keep unit economics flat as traffic grows.
Solo usersA $20 subscription beats the API until you start automating.

Frequently asked questions

Which model is best for writing?

For long-form writing Claude Sonnet 5 at $10 per 1M output tokens is the usual pick, with GPT-5.6 Terra close behind. Frontier models write marginally better and cost five times more.

Do I need a reasoning model for chat?

Rarely. Reasoning adds hidden thinking tokens that bill as output, so a plain chat model answers faster and cheaper for everyday questions.

How many words is a million tokens?

Roughly 700,000 English words. Arabic and other non-Latin scripts consume more tokens for the same text.

Can I mix models in one product?

Yes, and most production systems do. A cheap model handles the common path, a stronger one takes over on low confidence.

How do I estimate monthly cost?

Multiply expected output tokens by the output rate, add input at its own rate, then halve it if the workload is batchable.

Frequently searched

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