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
1

Claude Fable 5.1

Anthropic
Text & chatVisionReasoning
$10 / $501M tokensAPI only50View
2

GPT-6 Astra

OpenAI
Text & chatVisionReasoning
$10 / $501.05M tokensAPI only50View
3

GPT-6.1 Sol

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
4

GPT-6 Sol

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
5

GPT-6 Luna

OpenAI
Text & chatVisionReasoning
$0.1 / $0.51.05M tokensAPI only0.5View
6

Claude Opus 5.5

Anthropic
Text & chatVisionReasoning
$4 / $201M tokensAPI only20View
7

Claude Sonnet 5.5

Anthropic
Text & chatVisionReasoning
$2 / $101M tokensAPI only10View
8

Grok 4.7

xAI
Text & chatVisionReasoning
$2 / $6500K tokensAPI only6View
9

DeepSeek V4.1 Flash

DeepSeek
Text & chatVisionReasoning
$0.3 / $1.21M tokensAPI only1.2View
10

Qwen3.8 Max Prime

Qwen
Text & chatReasoningLong context 1M+
$3.36 / $10.081M tokensAPI only10.08View
11

GLM 5.3 FlashX

Z.ai
Text & chatVisionVideo
$0.37 / $1.251M tokensAPI only1.25View
12

Ember-1

Fireworks AI
Text & chatVisionReasoning
$3 / $151.04M tokensAPI only15View
13

Claude Opus 5

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
14

Claude Fable 5

Anthropic
Text & chatVisionReasoning
$10 / $501M tokensAPI only50View
15

GPT-5.6 Sol

OpenAI
Text & chatVisionReasoning
$4 / $201.05M tokensAPI only20View
16

GLM 5.3

Z.ai
Text & chatReasoningTool calling
$1.4 / $4.41.31M tokensAPI only4.4View
17

Grok 4.6

xAI
Text & chatVisionReasoning
$2 / $6500K tokensAPI only6View
18

Kimi K3

Moonshot AI
Text & chatVisionVideo
$3 / $151.05M tokensAPI only15View
19

GPT-5.6 Terra

OpenAI
Text & chatVisionReasoning
$2 / $121.05M tokensAPI only12View
20

Claude Opus 4.8

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View

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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