Technical Report No. 07

Grok 4.5 vs Fable 5 vs GPT-5.6 Sol

2026-07-12 · 23 tasks · 207 runs · $96.72 total · deterministic grading
Abstract.

Grok 4.5 leads at 91% from medium effort onward: high effort buys it nothing but a 31% larger bill. GPT-5.6 Sol is the only model whose accuracy climbs monotonically with effort (78→83→87%); Fable 5 oscillates at 85±2% regardless of the knob. The two frontier-hard tasks went 0-for-27.

Model card: Grok 4.5 vs Claude Fable 5 vs GPT-5.6 Sol across low, medium, and high effort on 23 v3 tasks
Card. Accuracy and cost-efficiency across nine configurations. Brown = Grok 4.5, blue = Claude Fable 5, gray = GPT-5.6 Sol; within each model, shades darken low → medium → high effort.

Grok owns the efficiency frontier; only Sol climbs with effort.

Grok owns the efficiency frontier; only Sol climbs with effort
Model (effort)Scorepass@1CostTokens/taskTime/task$/solved
Grok 4.5 (medium)21/2391.3%$6.67106 K3.9 min$0.32
Grok 4.5 (high)21/2391.3%$8.76141 K4.9 min$0.42
Claude Fable 5 (low)†20/2387.0%$12.1828 K3.4 min$0.61
GPT-5.6 Sol (high)20/2387.0%$15.9085 K4.2 min$0.80
Claude Fable 5 (high)†20/2387.0%$20.8244 K4.3 min$1.04
Grok 4.5 (low)19/2382.6%$3.3957 K2.5 min$0.18
GPT-5.6 Sol (medium)19/2382.6%$8.8350 K2.8 min$0.46
Claude Fable 5 (medium)†19/2382.6%$16.3236 K3.7 min$0.86
GPT-5.6 Sol (low)18/2378.3%$3.8523 K1.5 min$0.21

† Fable 5 ran with Opus 4.8 refusal fallback: 6 of 69 runs (8.7%) were declined by the API safety classifier (category cyber; the same three tasks at every effort) and served end-to-end by Opus 4.8; all six passed. Tokens are billed tokens; time is sandbox wall-clock.

1.

Grok plateaus at medium, and that’s the efficiency frontier. High effort spends 33% more tokens and 31% more money for the identical 21/23, failing the same two tasks. No config in the matrix beats 91.3% at $0.29/task.

2.

Only Sol rewards the effort knob. 78.3 → 82.6 → 87.0%, monotonic; each step buys real accuracy. Fable oscillates at 85±2% (87.0 → 82.6 → 87.0) with a different failure set each run, the knob changes which borderline tasks fall, not how many.

3.

Frugal tokens, premium price. Fable uses the fewest tokens at every effort (28 to 44 K/task, roughly half the agent steps of Grok) yet is the costliest per solved task ($0.61 to $1.04) at $10/$50-per-M pricing.

4.

The difficulty ceiling held; one wall fell. PennyLane Trotter fragmentation and SQLGlot internal-name canonicalization went 0-for-27 across all models and efforts. Flask’s teardown-error redesign fell to all three models, but only at high effort, making it the suite’s cleanest effort-discriminator.

Seven tasks that separated the field.

Seven tasks that separated the field
TaskGrok l/m/hFable l/m/hSol l/m/h
pennylane-trotter-fragmented× × ×× × ×× × ×
sqlglot-canonicalize-internal-names× × ×× × ×× × ×
flask-teardown-robust× ✓ ✓× ✓ ✓× × ✓
aiohttp-upgrade-deferred× ✓ ✓✓† ✓† ✓†× ✓ ✓
itertools-strip-prefix✓ ✓ ✓✓ ✓ ✓× × ×
networkx-leiden-communities✓ ✓ ✓✓ × ×✓ ✓ ✓
sqlglot-iso8601-nanos✓ ✓ ✓✓ × ✓✓ ✓ ✓

The remaining 16 tasks passed everywhere. † Fable cells on aiohttp-upgrade-deferred were served by the Opus 4.8 refusal fallback.

Twenty-three tasks from real merged pull requests (Python 9, Rust 4, TypeScript 4, JavaScript 3, Go 3: jiff, itertools, zod, hono, node-semver, cobra, pflag, chi, flask, aiohttp, sqlglot, packaging, more-itertools, networkx, pennylane), all merged after model training cutoffs, graded by deterministic hidden tests in a network-isolated Docker sandbox. One attempt per task per effort level (low, medium, high). Every task pre-validated: gold patch = 1.0, unpatched = 0.0, deterministic over 3 runs.

Pricing: Grok 4.5 $2/$6, GPT-5.6 Sol $5/$30, Claude Fable 5 $10/$50 per million tokens. Fable refusal fallback: VULCANBENCH_REFUSAL_FALLBACK=claude-opus-4-8.

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