What are the token costs and operational benchmarks for Fable 5?

Fable 5 is priced at $2.00 per million input tokens and $8.00 per million output tokens. It features a 512k token context window, an average response latency of 240ms TTFT, and achieves 58% on SWE-bench Verified and 81.5% on MMLU-Pro.
Verified daily via automated API latency tests and official documentation.
Input / 1M $2.00
Output / 1M $8.00
Context Limit 512k
TTFT Latency 240ms
SWE-bench 58%
Throughput 95 t/s

Architectural Overview

Frontier foundation model developed by Fable Studio featuring Generative Simulation & World Agent Engine architecture.

Optimal Production Use Cases

Long-horizon multi-agent world simulations, narrative engine synthesis, interactive character memory, and creative reasoning.

Interactive Monthly Token Economics & ROI Forecaster

Model your expected production workload across prompt (input) and completion (output) tokens.

Live Calculation Engine
10.0M Tokens
100K 50M 250M 500M+
2.5M Tokens
100K 10M 50M 100M+

Estimated Monthly Spend

Fable 5 $5.45

$2/1M in · $8/1M out

GPT-5.6 Luna $67.50

$0.18/1M in · $0.72/1M out

Projected Monthly Cost Reduction
$62.05 / mo
(91.9% lower cost)

Head-to-Head Comparisons Involving Fable 5

Versus Comparison

Fable 5 vs Claude 3.5 Haiku

Claude 3.5 Haiku is 60.0% cheaper for input tokens ($0.80 vs. $2.00 per 1M tokens) and $4.00 vs. $8.00 for output tokens (2.5x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (100ms faster than Fable 5). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 40.6% for Claude 3.5 Haiku.

Versus Comparison

Fable 5 vs Claude 3.5 Sonnet

Fable 5 is 33.3% cheaper for input tokens ($2.00 vs. $3.00 per 1M tokens) and $8.00 vs. $15.00 for output tokens (1.5x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (80ms faster than Claude 3.5 Sonnet). Claude 3.5 Sonnet leads coding benchmarks at 63.7% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs Claude 3.7 Sonnet

Fable 5 is 33.3% cheaper for input tokens ($2.00 vs. $3.00 per 1M tokens) and $8.00 vs. $15.00 for output tokens (1.5x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (410ms faster than Claude 3.7 Sonnet). Claude 3.7 Sonnet leads coding benchmarks at 70.3% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs Claude Opus 5

Fable 5 is 60.0% cheaper for input tokens ($2.00 vs. $5.00 per 1M tokens) and $8.00 vs. $25.00 for output tokens (2.5x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (100ms faster than Claude Opus 5). Claude Opus 5 leads coding benchmarks at 82.4% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs Codestral 25.01

Codestral 25.01 is 85.0% cheaper for input tokens ($0.30 vs. $2.00 per 1M tokens) and $0.90 vs. $8.00 for output tokens (6.7x cost difference). In terms of operational performance, Codestral 25.01 delivers faster response latency with 150ms TTFT (90ms faster than Fable 5). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 44.2% for Codestral 25.01.

Versus Comparison

Fable 5 vs Composer 2.5

Composer 2.5 is 10.0% cheaper for input tokens ($1.80 vs. $2.00 per 1M tokens) and $7.20 vs. $8.00 for output tokens (1.1x cost difference). In terms of operational performance, Composer 2.5 delivers faster response latency with 180ms TTFT (60ms faster than Fable 5). Composer 2.5 leads coding benchmarks at 74.6% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs DeepSeek-R1

DeepSeek-R1 is 72.5% cheaper for input tokens ($0.55 vs. $2.00 per 1M tokens) and $2.19 vs. $8.00 for output tokens (3.6x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (1560ms faster than DeepSeek-R1). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 49.2% for DeepSeek-R1.

Versus Comparison

Fable 5 vs DeepSeek-V3

DeepSeek-V3 is 93.0% cheaper for input tokens ($0.14 vs. $2.00 per 1M tokens) and $0.28 vs. $8.00 for output tokens (14.3x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (100ms faster than DeepSeek-V3). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 42.0% for DeepSeek-V3.

Versus Comparison

Fable 5 vs DeepSeek-V4 Flash

DeepSeek-V4 Flash is 93.0% cheaper for input tokens ($0.14 vs. $2.00 per 1M tokens) and $0.56 vs. $8.00 for output tokens (14.3x cost difference). In terms of operational performance, DeepSeek-V4 Flash delivers faster response latency with 150ms TTFT (90ms faster than Fable 5). DeepSeek-V4 Flash leads coding benchmarks at 62.4% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs Gemini 2.0 Flash

Gemini 2.0 Flash is 95.0% cheaper for input tokens ($0.10 vs. $2.00 per 1M tokens) and $0.40 vs. $8.00 for output tokens (20.0x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (140ms faster than Gemini 2.0 Flash). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 48.0% for Gemini 2.0 Flash.

Versus Comparison

Fable 5 vs Gemini 3.7 Flash

Gemini 3.7 Flash is 96.0% cheaper for input tokens ($0.08 vs. $2.00 per 1M tokens) and $0.32 vs. $8.00 for output tokens (25.0x cost difference). In terms of operational performance, Gemini 3.7 Flash delivers faster response latency with 75ms TTFT (165ms faster than Fable 5). Gemini 3.7 Flash leads coding benchmarks at 68.2% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs GLM 5.3 Flash

GLM 5.3 Flash is 92.5% cheaper for input tokens ($0.15 vs. $2.00 per 1M tokens) and $0.50 vs. $8.00 for output tokens (13.3x cost difference). In terms of operational performance, GLM 5.3 Flash delivers faster response latency with 130ms TTFT (110ms faster than Fable 5). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 54.2% for GLM 5.3 Flash.

Versus Comparison

Fable 5 vs OpenAI GPT-4o

Fable 5 is 20.0% cheaper for input tokens ($2.00 vs. $2.50 per 1M tokens) and $8.00 vs. $10.00 for output tokens (1.2x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (40ms faster than OpenAI GPT-4o). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 38.8% for OpenAI GPT-4o.

Versus Comparison

Fable 5 vs GPT-5.6 Luna

GPT-5.6 Luna is 91.0% cheaper for input tokens ($0.18 vs. $2.00 per 1M tokens) and $0.72 vs. $8.00 for output tokens (11.1x cost difference). In terms of operational performance, GPT-5.6 Luna delivers faster response latency with 90ms TTFT (150ms faster than Fable 5). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 48.5% for GPT-5.6 Luna.

Versus Comparison

Fable 5 vs GPT-5.6 Sol

Fable 5 is 75.0% cheaper for input tokens ($2.00 vs. $8.00 per 1M tokens) and $8.00 vs. $32.00 for output tokens (4.0x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (180ms faster than GPT-5.6 Sol). GPT-5.6 Sol leads coding benchmarks at 79.5% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs GPT-5.6 Terra

GPT-5.6 Terra is 25.0% cheaper for input tokens ($1.50 vs. $2.00 per 1M tokens) and $6.00 vs. $8.00 for output tokens (1.3x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (30ms faster than Fable 5). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs Grok 3

Fable 5 is 33.3% cheaper for input tokens ($2.00 vs. $3.00 per 1M tokens) and $8.00 vs. $15.00 for output tokens (1.5x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (610ms faster than Grok 3). Grok 3 leads coding benchmarks at 58.5% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs xAI Grok 4.6

Both models share identical input pricing at $2.00 per 1M tokens. In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (40ms faster than xAI Grok 4.6). xAI Grok 4.6 leads coding benchmarks at 76.8% SWE-bench vs. 58.0% for Fable 5.

Versus Comparison

Fable 5 vs Llama 3.3 70B Instruct

Llama 3.3 70B Instruct is 91.0% cheaper for input tokens ($0.18 vs. $2.00 per 1M tokens) and $0.40 vs. $8.00 for output tokens (11.1x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (180ms faster than Llama 3.3 70B Instruct). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 38.8% for Llama 3.3 70B Instruct.

Versus Comparison

Fable 5 vs Mistral Large 2

Both models share identical input pricing at $2.00 per 1M tokens. In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (310ms faster than Mistral Large 2). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 39.0% for Mistral Large 2.

Versus Comparison

Fable 5 vs OpenAI o1

Fable 5 is 86.7% cheaper for input tokens ($2.00 vs. $15.00 per 1M tokens) and $8.00 vs. $60.00 for output tokens (7.5x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (610ms faster than OpenAI o1). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 48.9% for OpenAI o1.

Versus Comparison

Fable 5 vs o3-mini

o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $8.00 for output tokens (1.8x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (960ms faster than o3-mini). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 49.3% for o3-mini.

Versus Comparison

Fable 5 vs Microsoft Phi-4 (14B)

Microsoft Phi-4 (14B) is 94.0% cheaper for input tokens ($0.12 vs. $2.00 per 1M tokens) and $0.36 vs. $8.00 for output tokens (16.7x cost difference). In terms of operational performance, Microsoft Phi-4 (14B) delivers faster response latency with 110ms TTFT (130ms faster than Fable 5). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 42.1% for Microsoft Phi-4 (14B).

Versus Comparison

Fable 5 vs Qwen 2.5 72B Instruct

Qwen 2.5 72B Instruct is 82.5% cheaper for input tokens ($0.35 vs. $2.00 per 1M tokens) and $0.40 vs. $8.00 for output tokens (5.7x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (180ms faster than Qwen 2.5 72B Instruct). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 44.0% for Qwen 2.5 72B Instruct.

Versus Comparison

Fable 5 vs Qwen 2.5 Max

Qwen 2.5 Max is 86.0% cheaper for input tokens ($0.28 vs. $2.00 per 1M tokens) and $0.84 vs. $8.00 for output tokens (7.1x cost difference). In terms of operational performance, Fable 5 delivers faster response latency with 240ms TTFT (240ms faster than Qwen 2.5 Max). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 44.2% for Qwen 2.5 Max.

Versus Comparison

Fable 5 vs Qwen 3.8 Flash Next

Qwen 3.8 Flash Next is 94.0% cheaper for input tokens ($0.12 vs. $2.00 per 1M tokens) and $0.48 vs. $8.00 for output tokens (16.7x cost difference). In terms of operational performance, Qwen 3.8 Flash Next delivers faster response latency with 120ms TTFT (120ms faster than Fable 5). Fable 5 leads coding benchmarks at 58.0% SWE-bench vs. 56.8% for Qwen 3.8 Flash Next.

Frequently Asked Questions & Query Fan-Out

How much does Fable 5 cost per 1M tokens?

Fable 5 costs $2.00 per million prompt (input) tokens and $8.00 per million completion (output) tokens.

What is the context window for Fable 5?

Fable 5 supports a maximum context window of 512,000 tokens, with a maximum single-generation output of 32,768 tokens.

What are the primary use cases for Fable 5?

Long-horizon multi-agent world simulations, narrative engine synthesis, interactive character memory, and creative reasoning.