Claude Fable 5.2 vs Llama 3.1 8B Instruct
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on November 14, 2026· 230 models
Claude Fable 5.2 is Anthropic's most capable model for the most demanding technical work, with gains over Fable 5.1 in coding, reasoning, and vision.
- Reasoning estimated
- ▲
- Speed estimated
- Input
- Output
- Context
- ▲1 M tokens
- Max output
- ▲128 K
- Input, $ per 1M tokens
- $8.00
- Output, $ per 1M tokens
- $40.00
- Cache read, $ per 1M
- $0.200
- Batch (input / output)
- $4.00 / $20.00
- Tool calling
- Yes
- Released
- ▲11/09/2026
- Knowledge cutoff
- 2026-06
- API id
- anthropic/claude-fable-5.2
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors.
- Reasoning estimated
- Speed estimated
- ▲
- Input
- Output
- Context
- 131 K tokens
- Max output
- 16 K
- Input, $ per 1M tokens
- ▲$0.020
- Output, $ per 1M tokens
- ▲$0.040
- Cache read, $ per 1M
- —
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- 07/23/2024
- Knowledge cutoff
- 2024-07
- API id
- meta-llama/llama-3.1-8b-instruct
Which is the better API choice: Claude Fable 5.2 vs Llama 3.1 8B Instruct?
- Llama 3.1 8B Instruct: cheapest input (100% less than Claude Fable 5.2)
- Llama 3.1 8B Instruct: cheapest output
- Claude Fable 5.2: largest context (1 M)
- Claude Fable 5.2: the newest (11/09/2026)
- Claude Fable 5.2: most reasoning (estimated)
- Llama 3.1 8B Instruct: the fastest (estimated)
Llama 3.1 8B Instruct costs 100% less on input and 100% less on output than Claude Fable 5.2 ($0.020 / $0.040 versus $8.00 / $40.00 per million tokens). Claude Fable 5.2 accepts more context (1 M). On capabilities, Claude Fable 5.2 accepts images; Claude Fable 5.2 has a reasoning mode. Claude Fable 5.2 offers a batch tier at half price for jobs that do not need an immediate answer.
What would your product cost?
Estimate the monthly cost with your app's real volume. List prices, no cache or batch discounts.
With Llama 3.1 8B Instruct you save $279.54 a month versus Claude Fable 5.2 (100% less).
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Paste your prompt: tokens and cost per model
Rough estimate (about 4 characters per token). Nothing is sent to any server.
Cost of sending it 1,000 times (input only)
- 1Llama 3.1 8B Instruct Meta$0.002
- 2Claude Haiku 5.5 Anthropic$0.008
- 3Claude Sonnet 5.5 Anthropic$0.152
- 4Claude Sonnet 5 Anthropic$0.152
- 5Claude Opus 5.5 Anthropic$0.304
- 6Claude Opus 5 Anthropic$0.380
- 7Claude Fable 5.2 Anthropic$0.608
- 8Claude Fable 5.1 Anthropic$0.760
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See allFrequently asked questions
Which is the better API choice: Claude Fable 5.2 vs Llama 3.1 8B Instruct?
Llama 3.1 8B Instruct costs 100% less on input and 100% less on output than Claude Fable 5.2 ($0.020 / $0.040 versus $8.00 / $40.00 per million tokens). Claude Fable 5.2 accepts more context (1 M). On capabilities, Claude Fable 5.2 accepts images; Claude Fable 5.2 has a reasoning mode. Claude Fable 5.2 offers a batch tier at half price for jobs that do not need an immediate answer.
Which is cheaper: Claude Fable 5.2 and Llama 3.1 8B Instruct?
Llama 3.1 8B Instruct is cheaper: $0.020 per million input tokens and $0.040 per million output tokens, versus $8.00 / $40.00 for Claude Fable 5.2.
Which has more context: Claude Fable 5.2 and Llama 3.1 8B Instruct?
Claude Fable 5.2 accepts 1 M tokens of context; Llama 3.1 8B Instruct accepts 131 K.
Which is newer: Claude Fable 5.2 and Llama 3.1 8B Instruct?
Claude Fable 5.2 was released on 11/09/2026; Llama 3.1 8B Instruct on 07/23/2024.
What would 10,000 requests a month cost with Claude Fable 5.2 and Llama 3.1 8B Instruct?
With 1,500 input and 400 output tokens per request: Claude Fable 5.2: $280.00; Llama 3.1 8B Instruct: $0.46 a month, at list price.
Where do the prices come from and how often are they updated?
From the public catalogs of OpenRouter, models.dev and LiteLLM, which publish each provider's list prices. They sync once a day and the last update date is shown above the comparison.
What does price per million tokens mean?
It is what the provider charges per million tokens you send (input) or the model generates (output). A token is roughly 4 characters. Output almost always costs more than input.
Sources: OpenRouter, models.dev and LiteLLM. Prices in USD per million tokens, list price, no volume discounts. Prompt tokens are an estimate; each provider's tokenizer may differ.