Updated November 13, 2026. Rank cannot separate these two. Price, access, and your workload decide. Public scores include evidence status and uncertainty.
Claude Fable 5.1 has the higher public score estimate, 79.21 versus 79.03, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 21 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Claude Fable 5.1: $10 input / $50 output
Gemini 4 Argon: $2 input / $10 output
Claude Fable 5.1: 1M
Gemini 4 Argon: 1M
Claude Fable 5.1: September 1, 2026
Gemini 4 Argon: September 30, 2026
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.
Code generation, repair, and software-engineering tasks
Claude Fable 5.1
Claude Fable 5.1 has the higher public coding point estimate, 73.9 to 71.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Tool use, computer use, and multi-step task completion
Claude Fable 5.1
Claude Fable 5.1 has the higher public agentic point estimate, 79.2 to 74.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
1K fresh input + 500 output tokens
Gemini 4 Argon
Gemini 4 Argon has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Gemini 4 Argon
Gemini 4 Argon has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 4 Argon
Gemini 4 Argon has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
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.
Like-for-like · BenchAlign v5.8
Claude Fable 5.1 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.
We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
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.
OSWorld 2.0Agentic
Normalized gap 27.5AutomationBenchAgentic
Normalized gap 19.9FrontierMath v2 (Tier 4)Math
Normalized gap 9.8FrontierMath v2 (Tiers 1-3)Math
Normalized gap 4.2ARC-AGI-2Reasoning
Normalized gap 1.3Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, reasoning, multimodal, 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.
| Category | Claude Fable 5.1 | Gemini 4 Argon | Basis | Reading |
|---|---|---|---|---|
| Agentic | 79.2Supported · #4/135 | 74.9Supported · #6/135 | Like-for-likeBenchAlign v5.8 lane · 19 vs 13 public rows | Claude Fable 5.1 leads · intervals overlap |
| Coding | 73.9Supported · #7/162 | 71.8Supported · #9/162 | Like-for-likeBenchAlign v5.8 lane · 13 vs 9 public rows | Claude Fable 5.1 leads · intervals overlap |
| Reasoning | 76.4Supported · #8/160 | 76.5Supported · #7/160 | Like-for-likeBenchAlign v5.8 lane · 4 vs 7 public rows | Practical tie |
| Knowledge | 84.1Supported · #5/180 | 79.2Supported · #8/180 | Like-for-likeBenchAlign v5.8 lane · 5 vs 2 public rows | Claude Fable 5.1 leads · intervals overlap |
| Multimodal | 80.5Estimated · #5/67 | Not ranked | Not comparableBenchAlign v5.8 lane · 11 vs 5 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 92.0Unranked · 2 rankable rows | 87.4Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 2 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, and knowledge denominators (BenchAlign v5.8) 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.
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.
1K fresh input + 500 output tokens
Gemini 4 Argon has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 4 Argon has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Gemini 4 Argon has the lower modeled cost
Costs use the listed standard API rates.
Enter a month of tokens to price it at both models’ listed API rates.
Standard listed rates, no batch or volume discounts.
Overall score against output price per 1M tokens, one model per family. Pricing as of November 12, 2026.
Claude Fable 5.1Gemini 4 Argon
Gray dots are the other priced models. The dark step line is the efficiency frontier: for a model under it, another model costs no more and scores at least as high.
See Gemini 4 Argon on the full price vs performance chartSourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Claude Fable 5.1
Gemini 4 Argon
Claude Fable 5.1
claude-fable-5-1
Anthropic Fable 5.1 and Mythos 5.1 launchGemini 4 Argon
gemini-4-argon
Google Gemini 4 Argon model documentationA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Fable 5.1
$0.25 per 1M cached input tokens
Anthropic Fable 5.1 launchGemini 4 Argon
$0.1 per 1M cached input tokens
Google Gemini API pricingClaude Fable 5.1
text, image
Anthropic Claude Fable 5.1 model pageGemini 4 Argon
text, image, video, audio, pdf
Google Gemini 4 Argon model documentationClaude Fable 5.1
Gemini 4 Argon
Claude Fable 5.1
Generally Available · Claude API, Claude products, AWS, Google Cloud, Microsoft Azure
Anthropic Fable 5.1 and Mythos 5.1 launchGemini 4 Argon
Generally Available · Gemini API, Google AI Studio
Google Gemini 4 Argon model documentationClaude Fable 5.1
Reasoning
Gemini 4 Argon
Reasoning
Claude Fable 5.1
Proprietary
Gemini 4 Argon
Proprietary
Claude Fable 5.1
Proprietary
Gemini 4 Argon
Proprietary
Claude Fable 5.1
2026-09-01
Gemini 4 Argon
2026-09-30
Claude Fable 5.1 has the higher public score estimate, 79.21 versus 79.03, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Claude Fable 5.1 has the higher public coding point estimate, 73.9 to 71.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Claude Fable 5.1 has the higher public agentic tasks point estimate, 79.2 to 74.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
For the stated presets, chat costs $0.035 on Claude Fable 5.1 and $0.007 on Gemini 4 Argon; repository review costs $0.65 and $0.13; the cache-heavy agent loop costs $0.75 and $0.16. Costs use the listed standard API rates.
Both models list the same context window, 1M.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 4.1
Not directly comparable
Terminal-Bench 4.0
Gemini 4 Argon leads this result
Terminal-Bench-Science 0.1
Not directly comparable
OSWorld 2.0
Gemini 4 Argon leads this result
AutomationBench
Gemini 4 Argon leads this result
Toolathlon-Verified
Not directly comparable
Toolathlon Verified Pass@3
Not directly comparable
Toolathlon Verified Pass³
Not directly comparable
Toolathlon Verified avg. turns
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Fable 5.1 leads this result
ApprenticeBench
Not directly comparable
CWE-bench v1
Shared sourceGemini 4 Argon leads this result
MazeBench
Gemini 4 Argon leads this result
OSWorld 2.1
Not directly comparable
WANDR
Not directly comparable
RoboDojo Sim
Shared sourceGemini 4 Argon leads this result
Remote Labor Index
Not directly comparable
OSWorld 2.1 Offline
Claude Fable 5.1 leads this result
DRACO
Not directly comparable
Finance Agent v2
Not directly comparable
Agents' Last Exam
Not directly comparable
Terminal-Bench-Science 0.1 (6x verifier timeout)
Not directly comparable
ExploitGym
Not directly comparable
CWE-bench
Not directly comparable
Bug Hunt Bench
Shared sourceClaude Fable 5.1 leads this result
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
SWE Multimodal
Not directly comparable
DeepSWE
Gemini 4 Argon leads this result
FrontierSWE v2
Shared sourceClaude Fable 5.1 leads this result
ProgramBench
Not directly comparable
CursorBench 3.2
Not directly comparable
LiveCodeBench (Vals)
Not directly comparable
CursorBench 4.0
Shared sourceGemini 4 Argon leads this result
PostTrainBench v1.1
Gemini 4 Argon leads this result
FrontierCode 2.0
Shared sourceClaude Fable 5.1 leads this result
VulcanBench Frontier v4
Not directly comparable
ScarfBench
Not directly comparable
Vibe Code Bench
Not directly comparable
PostTrainBench
Not directly comparable
ARC-AGI-1
Gemini 4 Argon leads this result
ARC-AGI-2
Gemini 4 Argon leads this result
GraphWalks BFS 256K–1M
Gemini 4 Argon leads this result
STEM Professor Bench
Not directly comparable
STEMBench
Not directly comparable
Graphwalks BFS 128K
Not directly comparable
ARC-AGI-3
Not directly comparable
ARC-AGI-3 Provider Adapter
Not directly comparable
ParseBench-1
Not directly comparable
Chartography (no tools)
Gemini 4 Argon leads this result
Chartography (tools)
Not directly comparable
BenchCAD Vision2Code (no tools)
Not directly comparable
BenchCAD Vision2Code (tools)
Not directly comparable
GDP.pdf (no tools)
Not directly comparable
GDP.pdf (tools)
Not directly comparable
OfficeQA
Not directly comparable
OfficeQA Pro
Not directly comparable
BenchCAD 2.1
Not directly comparable
BenchCAD 2.1 (tools)
Not directly comparable
ParseBench-2
Not directly comparable
ExtractBench Pro
Not directly comparable
LVBench
Not directly comparable
Blueprint-Bench 2
Not directly comparable
HLE
Not directly comparable
HLE w/o tools
Not directly comparable
GPQA Diamond (Vals)
Not directly comparable
MMLU-Pro (Vals)
Not directly comparable
PhysicianBench
Not directly comparable
LABBench2
Not directly comparable
Morphology-to-molecule matching
Not directly comparable
Gray Swan IPI (15 attempts)
Shared sourceGemini 4 Argon leads this result
FrontierMath v2 (Tiers 1-3)
Shared sourceClaude Fable 5.1 leads this result
FrontierMath v2 (Tier 4)
Shared sourceClaude Fable 5.1 leads this result
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 7,000+ subscribers.
Last updated November 13, 2026
