Claude Fable 5 vs GPT-5.6 Sol
Claude Fable 5 wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.
Verdict at a glance
Choose Claude Fable 5 if you…
- Strongest all-round reasoning
- Reliable long-context recall
- Top-tier coding
- Best for: Deep reasoning, Long documents, Coding
Choose GPT-5.6 Sol if you…
- Enhanced reasoning
- Strong code generation
- o-series architecture
- Best for: Reasoning-heavy tasks, Coding, Math
Head-to-head aggregate scores
Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.
Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.
Specs & pricing — every field side by side
List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.
| Dimension | Claude Fable 5 | GPT-5.6 Sol | Verdict |
|---|---|---|---|
| Vendor | Anthropic (US) | OpenAI (US) | Different vendors |
| Released | 2026.06 | 2026.07 | GPT-5.6 Sol is newer |
| Overall (rank) | 95 · #1 | 72 · #11 | Claude Fable 5 +23 |
| Coding | 99 · #1 | 88 · #3 | Claude Fable 5 +11 |
| Multimodal | 97 · #1 | 80 · #11 | Claude Fable 5 +17 |
| Context window | 1M | 1.05M | GPT-5.6 Sol larger |
| Max output | 128K | 128K | Tie |
| Effective-context | 98 | 88 | Claude Fable 5 more reliable |
| Input $/1M | $10 | $5 | GPT-5.6 Sol cheaper |
| Output $/1M | $50 | $30 | GPT-5.6 Sol cheaper |
| Cache discount | 90% off | 50% off | Claude Fable 5 deeper |
| Speed | ~30 tok/s | ~25 tok/s | Claude Fable 5 faster |
| TTFT | 1.2s | 2.0s | Claude Fable 5 snappier |
| Function calling | 92 | 93 | GPT-5.6 Sol ahead |
| Refusal rate | ~8% | ~14% | Claude Fable 5 less restrictive |
| English | 98 | 92 | Claude Fable 5 |
| Chinese | 82 | 74 | Claude Fable 5 |
| Modalities | text, image | text, image | Same |
| Open weights | No | No | Both closed |
| Fine-tuning | No | No | |
| Free tier | No free tier; $5 credit to start | No free API tier | |
| SOC2 / no-train | yes / yes | yes / yes | |
| Private deployment | No | No | Neither |
Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.
Dimension-by-dimension analysis
Reasoning & overall intelligence
Claude Fable 5 leads the overall aggregate by 23 points (95 vs 72). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while GPT-5.6 Sol remains a strong generalist that is not out of its depth on routine work.
Agentic coding
This is a clear gap: Claude Fable 5 scores 99 against 88. On multi-file edits, SWE-style tickets and long-horizon agent loops Claude Fable 5 needs fewer correction turns; GPT-5.6 Sol is still competent for scripts and assisted completion but trails as task complexity rises.
Multimodal
Claude Fable 5 leads multimodal 97 vs 80. Neither emits native video, so the comparison is about parsing images and documents, not generation.
Speed & latency
Claude Fable 5 is faster in interactive use: ~30 tok/s with 1.2s TTFT versus ~25 tok/s with 2.0s TTFT (about 1.2× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.
Context: window vs usable recall
Nominal windows are 1M for Claude Fable 5 and 1.05M for GPT-5.6 Sol. Crucially, the larger nominal window does not win on usable recall: GPT-5.6 Sol advertises 1.05M but Claude Fable 5 scores higher on effective-context (98 vs 88), i.e. it actually retains more of what it was given.
Price & total cost
GPT-5.6 Sol is the cheaper API at $5/$30 versus Claude Fable 5 at $10/$50 per 1M input/output tokens — list input is about 2.0× lower. Cache discounts (Claude Fable 5 90% vs GPT-5.6 Sol 50%) shift the effective bill, worked out below.
Chinese vs English
English: Claude Fable 5 98 vs GPT-5.6 Sol 92. Chinese: 82 vs 74. Both are US-based models; for Chinese-first workloads also compare domestic models on the leaderboard.
Tool use & ecosystem
Function-calling score: Claude Fable 5 92 vs GPT-5.6 Sol 93, so GPT-5.6 Sol has the edge on structured tool use. Neither offers standard fine-tuning. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.
Cost worked example — same workload, real token math
Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.
| Scenario · per month | Claude Fable 5 | GPT-5.6 Sol | Gap |
|---|---|---|---|
| List priceno cache applied | $2,500100M in × $10 + 30M out × $50 | $1,400100M in × $5 + 30M out × $30 | 1.79×gap |
| With caching90% of inputs cache-hit | $1,69090M cached in × $1 + 10M in × $10 + 30M out × $50 | $1,17590M cached in × $2.5 + 10M in × $5 + 30M out × $30 | 1.44×gap |
Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.