Fable 5 vs Grok 4.6 vs GPT-5.6 Sol vs Qwen3.8-Max: Who Actually Wins?

Grok 4.6 landed on August 12, 2026, and within a day X had turned it into a four-way (sometimes five-way) bake-off against Claude Fable 5, GPT-5.6 Sol, and Qwen3.8-Max — bug hunts, drawing tests, cost breakdowns, even a RuneScape leveling race. explainx.ai already covered Grok 4.6's official launch evals straight from SpaceXAI's model card. This piece pulls together the independent, third-party side of that comparison — three separate benchmarks plus the viral reaction threads — to see where each model actually leads, and where the marketing and the measurements diverge.

TL;DR

Bug Hunt Bench v10: 105 hidden bugs, two real repos

Product Compass's Paweł Huryn ran his Bug Hunt Bench the same day Grok 4.6 shipped — 105 bugs seeded across a VS Code extension repo (45) and an LMS repo (60), most reverted from real fix history, hunted by each model in its own native CLI, one round per repo. An independent judge scored every diff blind against a withheld answer key.

Bug Hunt Bench v10, Product Compass, August 12, 2026. 105 hidden bugs across two repos, 13 frontier models, 18 runs. 51 of the 105 bugs survived every model.

51 of the 105 seeded bugs survived every single model — none of the 13 frontier models tested caught them. That's the number worth sitting with before picking a winner from any single row.

Three reads jump out. First, GPT-5.6 Sol at effort MAX wins on raw fix count by a wide margin, but it also burned more wall-clock time (163 minutes) and budget than any of the other three models in this comparison — its own "high" re-run drops to 62 fixes for less than half the cost, which tells you effort tier matters more than model identity here. Second, Grok 4.6 is the value play: 42 bugs fixed in barely over half an hour for $22.73, the fastest wall clock of any top-tier run on the chart. Third, Fable 5 at effort MAX is the most expensive run on the entire chart — $104.49 for 34 fixes, worse cost-per-bug than GPT-5.6 Sol's best row.

Paweł Huryn's own read from the thread: "Looks like it may be my new default model. The best combination of time, value, and cost." — referring to Grok 4.6, with a note that Grok 4.7 is expected soon and "may be an even bigger jump." His posted headline numbers (Grok 4.5: 17 bugs with 10 non-planted finds; Grok 4.6: 27 with 15 non-planted; Fable 5: 29 with 2 non-planted) track the same direction as the fuller chart, with the "non-planted" figures — bugs the models flagged that weren't part of the seeded 105 — as a separate signal of how aggressively each model over-reports.

This is the same lesson explainx.ai flagged in Claude Code model vs effort: effort tier changes the answer as much as the model does. Compare rows at matched effort before crowning a winner.

RuneScape Bench: long-horizon agentic execution

A separate, unrelated benchmark — RuneScape Bench — scores peak XP-per-minute across in-game skills, ordered by difficulty, as a best-of-one proxy for sustained agentic execution over many steps with no shortcuts available.

RuneScape Bench, best-of-1 results, wide error margin per the publisher's own caveat.

Grok 4.6 posts the highest composite score in this table, ahead of Fable 5 by a meaningful margin — the inverse of the Bug Hunt Bench picture, where Fable trailed both Sol and Grok on cost-efficiency. Qwen3.8-Max does not appear in the published RuneScape Bench rows at all, so there's no direct read on how it handles long-horizon, no-shortcut agentic execution from this source. The benchmark's own caveat is worth repeating: this is best of 1, and the publisher explicitly asks readers to treat the numbers "with a wide error margin" — a single run per model, not an averaged score.

The takeaway isn't "Grok 4.6 is smarter than Fable 5." It's that bug-fixing accuracy and sustained multi-step execution are different skills, and a model can lead one while trailing the other. That distinction is exactly why explainx.ai's guide to reading AI benchmarks warns against collapsing a model's identity into a single leaderboard number.

Code Arena WebDev: a genuine three-way tie

LMArena's Arena.ai posted the Code Arena WebDev ranking after Grok 4.6 landed, and the picture there is closer than either of the other two benchmarks:

Per Arena.ai's own framing: "Grok 4.6 (High) is a big jump from Grok 4.5, which sits at #13 with 1553 pts. It's now on par with GPT-5.6 Sol xHigh (1622 pts) and Claude Fable 5 (1627 pts). All three currently land in the #5-7 rank range with only 4-9 pts of separation." Arena scores are community-voted, and Arena.ai's own note that the "picture will sharpen as more votes roll in" is worth taking at face value — a 4-9 point spread is inside typical confidence-interval noise on Elo-style arenas. Qwen3.8-Max isn't on this leaderboard either, which matches its absence from RuneScape Bench — its benchmark footprint so far leans on vendor-published and third-party API evals rather than these community arenas.

The jump from Grok 4.5's #13 to Grok 4.6's #7 is real and matches the official eval table's own +3.2 CursorBench and coding-benchmark gains covered in the Grok 4.6 launch post — but "on par with" is the accurate framing here, not "beats."

What the viral threads actually tested (and didn't)

A few caveats matter before quoting any of the social reaction threads as evidence for this specific four-way comparison, because two of the loudest ones didn't actually test Fable 5.

The banana drawing test (Ann Nguyen, @ann_nnng): gave Grok 4.6, Claude Opus 5, GPT-5.6 Sol, and Qwen3.8-Max a banana and asked each to be creative with an object-integrated drawing. Grok 4.6's standout answer treated the banana as a tiny island. A commenter's ranked preference on the thread: Opus 5 > Grok 4.6 > Qwen3.8-Max > GPT-5.6 Sol — one person's subjective call on one prompt, not a scored benchmark. Note the model set: this test used Claude Opus 5, not Fable 5. For an actual scored, cost-normalized drawing benchmark that does include Fable 5, see explainx.ai's coverage of the TryAI Canvas Arena, where GPT-5.6 Sol beat Fable 5 on drawing quality for roughly a twentieth of the cost.

The cost comparison (shirish, @shiri_shh): a video pitting Grok 4.6 against Claude Opus 5 on the same prompt, captioned "$1.80 vs $4.20." Reactions split — one commenter called Opus 5's output the clear win on color scheme, another pointed out that for less than half the price Grok's result "is really good," a third noted Grok's rendering skipped rain on a grass scene. Again, this compared Opus 5, not Fable 5 — but the direction (Grok landing meaningfully cheaper for comparable output) matches the Bug Hunt Bench cost pattern above, where Grok 4.6 undercut both Fable 5 and GPT-5.6 Sol's top-effort runs.

Treat both threads as color, not data — single prompts, no blind judging, subjective quality calls. They're useful for gut-check sentiment, not for ranking the four models in this comparison.

Pricing snapshot

Sticker price and cost-per-completed-task diverge the same way explainx.ai found comparing Claude Sonnet 5 against GPT-5.6 Luna: effort tier and token burn per task move the real dollar figure far more than the headline per-million rate does. Bug Hunt Bench v10 makes that visible directly — GPT-5.6 Sol's own MAX-effort and high-effort rows differ by more than 2x in cost for a 20-bug swing in results, without changing model identity at all.

When each model actually makes sense

Bottom line

No single model swept all three independent benchmarks. GPT-5.6 Sol wins on raw bug-fix accuracy when run at maximum effort, at a real cost premium. Grok 4.6 wins on cost-efficiency and long-horizon RuneScape execution, and lands in a statistical tie with Fable 5 and Sol on Code Arena WebDev. Fable 5 is the most expensive run on Bug Hunt Bench v10 but stays competitive on WebDev and close behind Grok 4.6 on RuneScape. Qwen3.8-Max trails the closed-lab trio on both speed and cost in the one benchmark where it appears alongside all three, and its differentiator — open weights — still hasn't shipped. Run your own workload before picking a default; a 4-9 point Arena gap and a 51-of-105 universal-miss rate on Bug Hunt Bench both say the same thing: none of these models has actually solved the problem yet.

Related on explainx.ai

• Grok 4.6 launch: official evals, pricing, Cursor access — SpaceXAI's own eval table this piece cross-checks against
• TryAI Canvas Arena: GPT-5.6 Sol beats Fable 5 at drawing — a scored, cost-normalized creativity benchmark that does include Fable 5
• Qwen3.8-Max: coding and cowork pitch, open weights still missing
• Qwen3.8-Max open weights go live on Hugging Face
• Claude Sonnet 5 vs GPT-5.6 Luna Max: cost comparison
• Kimi K3 vs Fable 5: vibe engineering stadium
• How to read AI benchmarks
• Claude Code model vs effort: knowing more vs trying harder
• Grok 4.7 training timeline: what Musk actually said

Sources: Product Compass Bug Hunt Bench v10, published August 12, 2026 (Paweł Huryn, @PawelHuryn) · RuneScape Bench, best-of-1 results · Arena.ai Code Arena WebDev leaderboard post, August 12, 2026 · Ann Nguyen (@ann_nnng) banana drawing thread · Shirish (@shiri_shh) cost comparison video · SpaceXAI Grok 4.6 launch announcement, August 12, 2026

Benchmark figures, pricing, and social reactions reflect August 13, 2026. Bug Hunt Bench, RuneScape Bench, and the X reaction threads are independent, largely single-run results, not audited multi-run benchmarks — treat exact numbers as directional and re-run your own workload before switching a production default.