Coding
Like-for-like- Claude Fable 5
- 76.9
- Supported · #2/183
- Laguna XS.2
- 25.2
- Supported · #178/183
- Basis
- BenchAlign lane · 10 vs 6 public rows
- Reading
- Claude Fable 5 leads
Claude Fable 5 vs Laguna XS.2
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Fable 5 has the higher public score, 80.9 versus 1.9, and the 90% score intervals do not overlap.
9 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Coding work
Code generation, repair, and software-engineering tasks
Claude Fable 5
Claude Fable 5 leads on the public coding lane, 76.9 to 25.2, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Long documents
Prompts that approach the documented context limit
Claude Fable 5
Claude Fable 5 has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Laguna XS.2 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
9 Claude Fable 5 only
9 Shared
1 Laguna XS.2 only
- Shared results
- 9
- Claude Fable 5 only
- 9
- Laguna XS.2 only
- 1
- Like-for-like categories
- 1 / 8
2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign 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
Directional only- Claude Fable 5
- 74.8
- Supported · #3/151
- Laguna XS.2
- 23.9
- Estimated · #148/151
- Basis
- BenchAlign lane · 4 vs 2 public rows
- Reading
- Directional only
Knowledge
Directional only- Claude Fable 5
- 83.5
- Supported · #2/181
- Laguna XS.2
- 18.8
- Estimated · #181/181
- Basis
- BenchAlign lane · 2 vs 2 public rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Fable 5
- 76.2
- #11/22
- Laguna XS.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Fable 5
- Not ranked
- Laguna XS.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Fable 5
- Not ranked
- Laguna XS.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Fable 5
- 62.5
- Unranked · 2 rankable rows
- Laguna XS.2
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Fable 5
- 78.3
- #54/120
- Laguna XS.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Fable 5 | Laguna XS.2 | Basis | Reading |
|---|---|---|---|---|
| Coding | 76.9Supported · #2/183 | 25.2Supported · #178/183 | Like-for-likeBenchAlign lane · 10 vs 6 public rows | Claude Fable 5 leads |
| Agentic | 74.8Supported · #3/151 | 23.9Estimated · #148/151 | Directional onlyBenchAlign lane · 4 vs 2 public rows | Directional only |
| Knowledge | 83.5Supported · #2/181 | 18.8Estimated · #181/181 | Directional onlyBenchAlign lane · 2 vs 2 public rows | Directional only |
| Reasoning | 76.2#11/22 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 62.5Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Instruction following | 78.3#54/120 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
Terminal-Bench 2.0
Agentic
SWE-bench Pro
Coding
SWE-bench Verified
Coding
MMLU-Pro (Vals)
Knowledge
LiveCodeBench (Vals)
Coding
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
- Laguna XS.2
- Self-hosted; infrastructure cost varies
- Fits in one request
Laguna XS.2 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Claude Fable 5
- $0.65
- Fits in one request
- Laguna XS.2
- Self-hosted; infrastructure cost varies
- Fits in one request
Laguna XS.2 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Fable 5
- $0.9
- Fits in one request
- Laguna XS.2
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Laguna XS.2 has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Fable 5Laguna XS.2
Context window
Maximum documented context; output-token limits may be lower.
Claude Fable 5
Laguna XS.2
256K
API model ID
Claude Fable 5
claude-fable-5
Anthropic model overviewLaguna XS.2
Not sourced
Cached-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 pricingLaguna XS.2
No comparable hosted API rate
Documented inputs
Claude Fable 5
text, image
Anthropic model overviewLaguna XS.2
Not sourced
Documented outputs
Claude Fable 5
Laguna XS.2
Not sourced
Provider availability
Claude Fable 5
Generally Available · Claude API
Anthropic model overviewLaguna XS.2
Not sourced
Reasoning profile
Claude Fable 5
Reasoning
Laguna XS.2
Reasoning
Weight access
Claude Fable 5
Proprietary
Laguna XS.2
Open Weight
License
Claude Fable 5
Proprietary
Laguna XS.2
Open Weight
Release date
Claude Fable 5
2026-06-09
Laguna XS.2
2026-04-28
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, 80.9 versus 1.9, and the 90% score intervals do not overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Claude Fable 5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence19 rows
Agentic
Terminal-Bench 3.0
Claude Fable 534.0%SourceLaguna XS.2—Not directly comparable
Terminal-Bench 2.0
Claude Fable 584.3%SourceLaguna XS.235.7%SourceClaude Fable 5 leads this result
OSWorld-Verified
Claude Fable 585%SourceLaguna XS.2—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Fable 580.5%SourceLaguna XS.225.8%SourceClaude Fable 5 leads this result
Coding
SWE-bench Verified
Claude Fable 595%SourceLaguna XS.269.9%SourceClaude Fable 5 leads this result
SWE-bench Pro
Claude Fable 580%SourceLaguna XS.246.3%SourceClaude Fable 5 leads this result
FrontierSWE v2
Claude Fable 548.0%SourceLaguna XS.2—Not directly comparable
FrontierCode 1.1 Main
Claude Fable 553.5%SourceLaguna XS.2—Not directly comparable
Terminal-Bench 2.0
Claude Fable 584.3%SourceLaguna XS.235.7%SourceClaude Fable 5 leads this result
cursorBench31
Claude Fable 570.6%SourceLaguna XS.2—Not directly comparable
cursorBench32
Claude Fable 570.5%SourceLaguna XS.2—Not directly comparable
VulcanBench v3
Claude Fable 589.5%SourceLaguna XS.2—Not directly comparable
LiveCodeBench (Vals)
Claude Fable 589.8%SourceLaguna XS.267.8%SourceClaude Fable 5 leads this result
SWE-bench (Vals)
Claude Fable 595.0%SourceLaguna XS.255.2%SourceClaude Fable 5 leads this result
SWE Multilingual
Claude Fable 5—Laguna XS.257.7%SourceNot directly comparable
Knowledge
Multimodal
Frequently asked questions
Which is better, Claude Fable 5 or Laguna XS.2?
Claude Fable 5 has the higher public score, 80.9 versus 1.9, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, Claude Fable 5 or Laguna XS.2?
Claude Fable 5 leads the public coding lane, 76.9 to 25.2, with Supported evidence for both models and non-overlapping 90% intervals.
Which is better for agentic tasks, Claude Fable 5 or Laguna XS.2?
Claude Fable 5 scores higher for agentic tasks on the public lane, 74.8 to 23.9. Laguna XS.2 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Claude Fable 5 or Laguna XS.2?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Claude Fable 5 or Laguna XS.2?
Claude Fable 5 has the larger documented context window: 1M, compared with 256K.
Related comparisons
Last updated September 4, 2026
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