AI Models · Paid vs Paid

Claude Fable 5 (batch) Paid vs Mistral Large Paid

Claude Fable 5 (batch) vs Mistral Large compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

Claude Fable 5 (batch)PaidAnthropic
$5 /M input
$25 /M outputManaged API (no infra to run)
TypeProprietary
Context window1M tokens
MultimodalYes
Self-hostNo
Mistral LargePaidMistral AI
$2 /M input
$6 /M outputManaged API (no infra to run)
TypeProprietary
Context window128K tokens
MultimodalNo
Self-hostNo
Choose Mistral Large for the lower output price ($6/M vs $25/M). Choose Claude Fable 5 (batch) if you need the larger 1M context window.

Claude Fable 5 (batch) vs Mistral Large specs

SpecClaude Fable 5 (batch)Mistral LargeWinner
MakerAnthropicMistral AI
TypeProprietaryProprietary
Context window1M tokens128K tokensClaude Fable 5 (batch)
Input price$5/M$2/MMistral Large
Output price$25/M$6/MMistral Large
Vision / multimodalYesNoClaude Fable 5 (batch)
Tool / function callingYesYes= Tie
Self-hostableNo (API only)No (API only)
LicenseProprietaryProprietary

Price gap & when to choose each

4.2×cheaper per output token

Mistral Large is ~4.2× cheaper than Claude Fable 5 (batch) on output tokens ($6 vs $25 per M tokens).

Choose Claude Fable 5 (batch) if…
  • You want frontier performance through a managed API
  • You need the longer 1M context window
  • You value reliability & ecosystem
  • You don't want to manage infrastructure
Choose Mistral Large if…
  • You want frontier performance through a managed API
  • You want the lower output price
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityClaude Fable 5 (batch)Mistral Large
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Claude Fable 5 (batch) vs Mistral Large

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

Claude Fable 5 (batch)
Mistral Large
Intelligence index
49.7
6.8
Coding index
76.5
GPQA
92.6%
47.2%
Humanity's Last Exam
55.5%
2.9%
Long Context Reasoning
82.3%
2%
SciCode
61%
IFBench
63.5%
31.6%
τ²-Bench
98.5%
33%
τ-Bench Banking
38.1%
Terminal-Bench
84.6%
Terminal-Bench Hard
62.9%
Math index
0
MMLU-Pro
68.3%
LiveCodeBench
26.7%
MATH-500
71.4%
AIME
9.3%
AIME 2025
0%
Speed
70 tok/s
0 tok/s
Latency
60.71s
0s
Intelligence per $
2.5
2.3

Benchmark data by Artificial Analysis.

How Claude Fable 5 (batch) and Mistral Large score

🏆 Best value & openness: Claude Fable 5 (batch) (3.1 vs 2.7 / 5)
CriterionClaude Fable 5 (batch)Mistral Large
Cost-efficiency3.04.0
Context window5.03.5
Openness1.51.5
Self-hosting1.01.0
Multimodality5.03.5

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

Claude Fable 5 (batch) Paid

Anthropic · Proprietary

Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and...

Mistral Large Paid

Mistral AI · Proprietary

This is Mistral AI's flagship model, Mistral Large 2 (version `mistral-large-2407`). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news

Frequently asked questions

Claude Fable 5 (batch) vs Mistral Large — which is cheaper?

Mistral Large is cheaper on output ($6/M vs $25/M).

Which has the larger context window?

Claude Fable 5 (batch) offers the larger context window (1M tokens).

Claude Fable 5 (batch) vs Mistral Large — which should I pick in 2026?

Choose Mistral Large for the lower output price ($6/M vs $25/M). Choose Claude Fable 5 (batch) if you need the larger 1M context window.

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