Grok 4.5 vs Claude Fable 5
A comparison of xAI's Grok 4.5, a coding- and agent-focused model trained with Cursor, against Anthropic's Claude Fable 5, the current benchmark leader on the hardest coding evaluations.
Quick Answer
Claude Fable 5 leads on the hardest coding and reasoning benchmarks; Grok 4.5 delivers near-frontier results at roughly a fifth of the cost and with far fewer tokens per completed task, but with a notably higher hallucination rate.
Reviewed by TechLogHub Engineering Team. Last updated October 6, 2026. Updated for Grok 4.5's July 8, 2026 launch pricing and benchmark figures, and Claude Fable 5's restored worldwide access as of July 1, 2026.
| Feature |  Claude Fable 5 | |
|---|---|---|
| Developed By | xAI (SpaceX) | Anthropic |
| Model Class | Flagship coding/agentic frontier model | Mythos-class single frontier model |
| Context Window | 500K tokens | 1M tokens input, up to 128K output |
| Training Hardware | Tens of thousands of Nvidia GB300 GPUs | Not publicly disclosed |
| Pricing | $2 / $6 per million input/output tokens | $10 / $50 per million input/output tokens |
| Token Efficiency | ~1.9M tokens per Coding Agent Index task | ~7.2M tokens per Coding Agent Index task |
| Release Date | July 8, 2026 | June 9, 2026 (restored access July 1, 2026) |
| Primary Use Case | Cost-efficient autonomous coding agents and tool-calling workflows | Accuracy-critical coding, long-horizon agentic work, life sciences research |
Grok 4.5
xAI's flagship model for coding, agentic tool use, and knowledge work, released July 8, 2026 and trained in part on data from Cursor, the AI code editor SpaceX/xAI acquired earlier in 2026.
Pros
- Roughly 5x cheaper per token than Fable 5 ($2/$6 vs $10/$50 per million tokens)
- Highly token-efficient — averages ~1.9M tokens per coding task vs Fable 5's ~7.2M
- Wins several agentic benchmarks outright (AutomationBench-AA, SWE Marathon) against both Fable 5 and Opus 4.8
- Fast serving speed (~80 tokens/second) and quick task completion in hands-on tests
- 500K-token context window with prompt caching and function calling
- Deep integration with Cursor given the shared training lineage
Cons
- Notably higher hallucination rate — jumped from 25% to 54% on one knowledge benchmark as accuracy improved
- Trails Fable 5 clearly on the hardest coding benchmark, SWE-Bench Pro (64.7% vs 80.4%)
- Highest guardrail-violation rate among compared models on finance-domain agent tasks
- Newer, less battle-tested in production than Anthropic's more mature model lineage
- EU availability lagged the initial US/global launch
Best For
High-volume agentic workloads and cost-sensitive teams where near-frontier accuracy at a fraction of the price outweighs owning the single top benchmark score, and where outputs get human or automated review before shipping.
Claude Fable 5
Anthropic's most capable widely released Mythos-class model, restored to worldwide access July 1, 2026 after a brief export-control suspension, built for demanding reasoning, coding, and long-horizon agentic work.
Pros
- Leads the hardest coding benchmark, SWE-Bench Pro, by a wide margin (80.4% vs 64.7%)
- Meaningfully lower hallucination rate in independent evaluations
- 1M-token context window, roughly double Grok 4.5's
- Deep, mature integration across Claude Code, Claude Platform, and major clouds
- Anthropic has invested heavily in alignment, which shows in lower guardrail-violation rates
Cons
- Roughly 5x more expensive per token than Grok 4.5
- Uses far more tokens to complete equivalent coding tasks (~7.2M vs ~1.9M)
- Was inaccessible for roughly three weeks in June 2026 due to export controls
- Slower in head-to-head hands-on coding tests in independent reviews
Best For
Teams where coding accuracy and reliability on the hardest problems matter more than cost, and where the premium price is justified by fewer errors needing correction downstream.
The Cost-of-Intelligence Story
Grok 4.5's headline is price: at $2/$6 per million tokens against Fable 5's $10/$50, and using roughly 3.8x fewer tokens per completed coding task, the effective cost gap on a finished task is far larger than the sticker price alone suggests — independent measurements put a completed Coding Agent Index task at roughly $2.49 on Grok 4.5 versus $11.80 on Fable 5, a difference of about 79%.
Where the Accuracy Gap Actually Shows Up
On easier benchmarks like Terminal-Bench 2.1, the two models are within about a point of each other (84.3% Fable 5 vs 83.3% Grok 4.5). The gap widens on the hardest tasks: DeepSWE 1.1 (real GitHub issue resolution) shows Fable 5 at 70% vs Grok 4.5 at 53%, and SWE-Bench Pro shows an even larger 15.7-point gap. This suggests Grok 4.5 is a strong generalist that starts to lag specifically on the most demanding, multi-step engineering problems.
The Hallucination Trade-off
Grok 4.5's accuracy on the AA-Omniscience knowledge index rose from 35% to 52% over its predecessor, but its hallucination rate more than doubled from 25% to 54% in the same evaluation — meaning the model knows more but is also more confident when it's wrong. For production deployments in regulated or customer-facing contexts, this is a real risk that the raw benchmark numbers don't fully capture, and it's a gap where Fable 5 currently holds a clearer advantage.
Agentic and Tool-Use Performance
Grok 4.5 actually leads Fable 5 and Opus 4.8 on some agentic evaluations — notably AutomationBench-AA (51.4% vs 48.6% for Fable 5) and SWE Marathon, a long-horizon software engineering benchmark (29.0% vs 24.0%). But it also logs a higher rate of guardrail violations per task (0.63 vs lower rates for Anthropic models), which matters more for agents operating near live financial or production systems than for exploratory coding work.
Verdict
Choose Grok 4.5 if you're running high-volume agentic or coding workloads where cost and speed dominate and you have review steps to catch occasional hallucinations. Choose Claude Fable 5 if you're solving the hardest coding and reasoning problems where accuracy directly translates to fewer costly mistakes, and the premium price is worth it.