Coding work
Code generation, repair, and software-engineering tasks
Claude Fable 5
Claude Fable 5 leads on the public coding lane, 74.5 to 64.7, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Claude Fable 5 vs GPT-5.6 Terra
Updated September 24, 2026. Rank says Claude Fable 5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Share or export
Decision reading
Claude Fable 5 has the higher public score estimate, 79.07 versus 72.58, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 13 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 13
- Claude Fable 5 only
- 8
- GPT-5.6 Terra only
- 19
- Like-for-like categories
- 3 / 8
Supported: Claude Fable 5 and GPT-5.6 TerraHow the comparison works
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Agentic work
Tool use, computer use, and multi-step task completion
Claude Fable 5
Claude Fable 5 leads on the public agentic lane, 73.7 to 59.5, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: strongerLong documents
Prompts that approach the documented context limit
GPT-5.6 Terra
GPT-5.6 Terra has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Chat turn cost
1K fresh input + 500 output tokens
GPT-5.6 Terra
GPT-5.6 Terra has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
GPT-5.6 Terra
GPT-5.6 Terra has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesRepository review cost
50K fresh input + 3K output tokens
GPT-5.6 Terra
GPT-5.6 Terra has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
74.5Claude Fable 564.7GPT-5.6 Terra
Like-for-like · BenchAlign v5.7
Claude Fable 5 leads the like-for-like coding row, although the 90% intervals overlap.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
8 Claude Fable 5 only
13 Shared
19 GPT-5.6 Terra only
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
SWE-bench ProCoding
Normalized gap 16.6Claude Fable 5:80%GPT-5.6 Terra:63.4%cursorBench32Coding
Normalized gap 5.6Claude Fable 5:70.5%GPT-5.6 Terra:64.9%ARC-AGI-2Reasoning
Normalized gap 5.3Claude Fable 5:89.2%GPT-5.6 Terra:83.9%MMLU-Pro (Vals)Knowledge
Normalized gap 4.8Claude Fable 5:91.5%GPT-5.6 Terra:86.7%LiveCodeBench (Vals)Coding
Normalized gap 3.9Claude Fable 5:89.8%GPT-5.6 Terra:85.9%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.7 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Agentic
Like-for-like- Claude Fable 5
- 73.7
- Supported · #4/105
- GPT-5.6 Terra
- 59.5
- Supported · #18/105
- Basis
- BenchAlign v5.7 lane · 5 vs 9 public rows
- Reading
- Claude Fable 5 leads
Coding
Like-for-like- Claude Fable 5
- 74.5
- Supported · #4/135
- GPT-5.6 Terra
- 64.7
- Supported · #8/135
- Basis
- BenchAlign v5.7 lane · 10 vs 8 public rows
- Reading
- Claude Fable 5 leads · intervals overlap
Knowledge
Like-for-like- Claude Fable 5
- 81.8
- Supported · #4/158
- GPT-5.6 Terra
- 71.1
- Supported · #9/158
- Basis
- BenchAlign v5.7 lane · 2 vs 8 public rows
- Reading
- Claude Fable 5 leads · intervals overlap
Instruction following
Directional only- Claude Fable 5
- 75.7
- #58/124
- GPT-5.6 Terra
- 85.7
- #35/124
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Fable 5
- 80.6
- Unranked · 4 rankable rows
- GPT-5.6 Terra
- 65.4
- #12/19
- Basis
- Provisional lane · 1 vs 2 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Fable 5
- 62.6
- Unranked · 2 rankable rows
- GPT-5.6 Terra
- 77.2
- #16/50
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Fable 5
- Not ranked
- GPT-5.6 Terra
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Fable 5
- Not ranked
- GPT-5.6 Terra
- 96.8
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
| Category | Claude Fable 5 | GPT-5.6 Terra | Basis | Reading |
|---|---|---|---|---|
| Agentic | 73.7Supported · #4/105 | 59.5Supported · #18/105 | Like-for-likeBenchAlign v5.7 lane · 5 vs 9 public rows | Claude Fable 5 leads |
| Coding | 74.5Supported · #4/135 | 64.7Supported · #8/135 | Like-for-likeBenchAlign v5.7 lane · 10 vs 8 public rows | Claude Fable 5 leads · intervals overlap |
| Knowledge | 81.8Supported · #4/158 | 71.1Supported · #9/158 | Like-for-likeBenchAlign v5.7 lane · 2 vs 8 public rows | Claude Fable 5 leads · intervals overlap |
| Instruction following | 75.7#58/124 | 85.7#35/124 | Directional onlyProvisional lane · 0 vs 0 weighted rows | Directional only |
| Reasoning | 80.6Unranked · 4 rankable rows | 65.4#12/19 | Not comparableProvisional lane · 1 vs 2 weighted rows | Not comparable |
| Multimodal | 62.6Unranked · 2 rankable rows | 77.2#16/50 | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 96.8Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Claude Fable 5
- $0.035
- Fits in one request
- GPT-5.6 Terra
- $0.008
- Fits in one request
GPT-5.6 Terra has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Fable 5
- $0.65
- Fits in one request
- GPT-5.6 Terra
- $0.136
- Fits in one request
GPT-5.6 Terra has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Fable 5
- $0.9
- Fits in one request
- GPT-5.6 Terra
- $0.2
- Fits in one request
GPT-5.6 Terra has the lower modeled cost
Costs use the listed standard API rates.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Fable 5GPT-5.6 Terra
Context window
Maximum documented context; output-token limits may be lower.
Claude Fable 5
GPT-5.6 Terra
1.05M
OpenAI model catalogAPI model ID
Claude Fable 5
claude-fable-5
Anthropic model overviewGPT-5.6 Terra
gpt-5.6-terra
OpenAI model catalogCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Fable 5
$1 per 1M cached input tokens
Claude API pricingGPT-5.6 Terra
$0.2 per 1M cached input tokens
OpenAI pricingDocumented inputs
Claude Fable 5
text, image
Anthropic model overviewGPT-5.6 Terra
text, image
OpenAI model catalogDocumented outputs
Claude Fable 5
GPT-5.6 Terra
Provider availability
Claude Fable 5
Generally Available · Claude API
Anthropic model overviewGPT-5.6 Terra
Generally Available · OpenAI Responses API
OpenAI model catalogReasoning profile
Claude Fable 5
Reasoning
GPT-5.6 Terra
Reasoning
Weight access
Claude Fable 5
Proprietary
GPT-5.6 Terra
Proprietary
License
Claude Fable 5
Proprietary
GPT-5.6 Terra
Proprietary
Release date
Claude Fable 5
2026-06-09
GPT-5.6 Terra
2026-07-09
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- Claude Fable 5 has the higher public score estimate, 79.07 versus 72.58, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.65 vs $0.136. Cache-heavy agent loop: $0.9 vs $0.2.
- Context tradeoff
- GPT-5.6 Terra has the larger documented window (1.05M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Fable 5 or GPT-5.6 Terra?
Claude Fable 5 has the higher public score estimate, 79.07 versus 72.58, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Claude Fable 5 or GPT-5.6 Terra?
Claude Fable 5 leads the public coding lane, 74.5 to 64.7, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Claude Fable 5 or GPT-5.6 Terra?
Claude Fable 5 leads the public agentic tasks lane, 73.7 to 59.5, with Supported evidence for both models and non-overlapping 90% intervals.
Which costs less, Claude Fable 5 or GPT-5.6 Terra?
For the stated presets, chat costs $0.035 on Claude Fable 5 and $0.008 on GPT-5.6 Terra; repository review costs $0.65 and $0.136; the cache-heavy agent loop costs $0.9 and $0.2. Costs use the listed standard API rates.
Which has the larger context window, Claude Fable 5 or GPT-5.6 Terra?
GPT-5.6 Terra has the larger documented context window: 1.05M, compared with 1M.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence40 rows
Agentic
Terminal-Bench 3.0
Shared sourceClaude Fable 534.0%GPT-5.6 Terra20.8%Claude Fable 5 leads this result
Terminal-Bench 2.1
Claude Fable 584.3%SourceGPT-5.6 Terra87.4%SourceGPT-5.6 Terra leads this result
OSWorld-Verified
Claude Fable 585%SourceGPT-5.6 Terra—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Fable 580.5%SourceGPT-5.6 Terra77.5%SourceClaude Fable 5 leads this result
ApprenticeBench
Shared sourceClaude Fable 534%GPT-5.6 Terra16%Claude Fable 5 leads this result
BrowseComp
Claude Fable 5—GPT-5.6 Terra87.5%SourceNot directly comparable
OSWorld 2.0
Claude Fable 5—GPT-5.6 Terra50.2%SourceNot directly comparable
CyberGym
Claude Fable 5—GPT-5.6 Terra81.8%SourceNot directly comparable
ExploitGym
Claude Fable 5—GPT-5.6 Terra23.2%SourceNot directly comparable
Toolathlon
Claude Fable 5—GPT-5.6 Terra53.1%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Fable 595%SourceGPT-5.6 Terra—Not directly comparable
SWE-bench Pro
Claude Fable 580%SourceGPT-5.6 Terra63.4%SourceClaude Fable 5 leads this result
FrontierSWE v2
Claude Fable 547.0%SourceGPT-5.6 Terra—Not directly comparable
FrontierCode 1.1 Main
Claude Fable 553.5%SourceGPT-5.6 Terra—Not directly comparable
Terminal-Bench 2.1
Claude Fable 584.3%SourceGPT-5.6 Terra87.4%SourceGPT-5.6 Terra leads this result
cursorBench31
Claude Fable 570.6%SourceGPT-5.6 Terra—Not directly comparable
cursorBench32
Shared sourceClaude Fable 570.5%GPT-5.6 Terra64.9%Claude Fable 5 leads this result
VulcanBench v3
Claude Fable 589.5%SourceGPT-5.6 Terra87.0%SourceClaude Fable 5 leads this result
LiveCodeBench (Vals)
Claude Fable 589.8%SourceGPT-5.6 Terra85.9%SourceClaude Fable 5 leads this result
SWE-bench (Vals)
Claude Fable 595.0%SourceGPT-5.6 Terra95.4%SourceGPT-5.6 Terra leads this result
DeepSWE
Claude Fable 5—GPT-5.6 Terra69.6%SourceNot directly comparable
FrontierCode 1.1 Extended
Claude Fable 5—GPT-5.6 Terra55.8%SourceNot directly comparable
Reasoning
Multimodal
Blueprint-Bench 2
Claude Fable 538.6%SourceGPT-5.6 Terra—Not directly comparable
OfficeQA Pro
Claude Fable 557.9%SourceGPT-5.6 Terra—Not directly comparable
MMMU-Pro
Claude Fable 5—GPT-5.6 Terra80.7%SourceNot directly comparable
MMMU-Pro w/ Python
Claude Fable 5—GPT-5.6 Terra82%SourceNot directly comparable
Knowledge
GPQA Diamond (Vals)
Claude Fable 593.2%SourceGPT-5.6 Terra90.9%SourceClaude Fable 5 leads this result
MMLU-Pro (Vals)
Claude Fable 591.5%SourceGPT-5.6 Terra86.7%SourceClaude Fable 5 leads this result
GPQA
Claude Fable 5—GPT-5.6 Terra92.9%SourceNot directly comparable
GPQA-D
Claude Fable 5—GPT-5.6 Terra92.9%SourceNot directly comparable
HLE-Verified
Claude Fable 5—GPT-5.6 Terra51.1%SourceNot directly comparable
LABBench2
Claude Fable 5—GPT-5.6 Terra81.2%SourceNot directly comparable
HealthBench Professional
Claude Fable 5—GPT-5.6 Terra57.7%SourceNot directly comparable
HealthBench Hard
Claude Fable 5—GPT-5.6 Terra32.7%SourceNot directly comparable
Math
40 public results · 13 shared
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Last updated September 24, 2026