Updated October 7, 2026. Rank says Claude Sonnet 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
Claude Sonnet 5 has the higher public score estimate, 65.89 versus 63.97, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 11 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
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 Sonnet 5
Claude Sonnet 5 has the higher public coding point estimate, 59 to 57.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Tool use, computer use, and multi-step task completion
Claude Sonnet 5
Claude Sonnet 5 has the higher public agentic point estimate, 64.8 to 57.6, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Prompts that approach the documented context limit
Claude Sonnet 5
Claude Sonnet 5 has the larger documented context window.
1K fresh input + 500 output tokens
Grok 4.5
Grok 4.5 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
Grok 4.5
Grok 4.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Grok 4.5
Grok 4.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
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 Sonnet 5 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.
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.
CursorBench 3.2Coding
Normalized gap 5.2LiveCodeBench (Vals)Coding
Normalized gap 5.0MMLU-Pro (Vals)Knowledge
Normalized gap 1.7SWE-bench ProCoding
Normalized gap 1.5SWE MultilingualCoding
Normalized gap 0.3Each row shows the public-lane category score for both models: the BenchAlign v5.8 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.
| Category | Claude Sonnet 5 | Grok 4.5 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 64.8Supported · #16/122 | 57.6Supported · #29/122 | Like-for-likeBenchAlign v5.8 lane · 7 vs 4 public rows | Claude Sonnet 5 leads · intervals overlap |
| Coding | 59.0Supported · #24/146 | 57.7Supported · #27/146 | Like-for-likeBenchAlign v5.8 lane · 11 vs 8 public rows | Claude Sonnet 5 leads · intervals overlap |
| Knowledge | 64.0Supported · #29/174 | 67.0Supported · #19/174 | Like-for-likeBenchAlign v5.8 lane · 6 vs 2 public rows | Grok 4.5 leads · intervals overlap |
| Reasoning | 78.7Unranked · 2 rankable rows | 50.4#28/28 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Multimodal | 78.4#15/49 | 79.5Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 0 weighted 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 | Not ranked | 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 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
Grok 4.5 has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Grok 4.5 has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Grok 4.5 has the lower modeled cost
Costs use the listed standard API rates.
Sourced 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 Sonnet 5
Grok 4.5
500K
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewGrok 4.5
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 5
$0.2 per 1M cached input tokens
Claude API pricingGrok 4.5
$0.3 per 1M cached input tokens
Claude Sonnet 5
text, image
Anthropic model overviewGrok 4.5
Not sourced
Claude Sonnet 5
Grok 4.5
Not sourced
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewGrok 4.5
Not sourced
Claude Sonnet 5
Reasoning
Grok 4.5
Reasoning
Claude Sonnet 5
Proprietary
Grok 4.5
Proprietary
Claude Sonnet 5
Proprietary
Grok 4.5
Proprietary
Claude Sonnet 5
2026-06-30
Grok 4.5
2026-07-08
Claude Sonnet 5 has the higher public score estimate, 65.89 versus 63.97, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Claude Sonnet 5 has the higher public coding point estimate, 59 to 57.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Claude Sonnet 5 has the higher public agentic tasks point estimate, 64.8 to 57.6, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
For the stated presets, chat costs $0.007 on Claude Sonnet 5 and $0.005 on Grok 4.5; repository review costs $0.13 and $0.118; the cache-heavy agent loop costs $0.18 and $0.16. Costs use the listed standard API rates.
Claude Sonnet 5 has the larger documented context window: 1M, compared with 500K.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 3.0
Shared sourceGrok 4.5 leads this result
Terminal-Bench 2.1
Grok 4.5 leads this result
BrowseComp
Not directly comparable
HLE w/ tools
Not directly comparable
OSWorld-Verified
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Sonnet 5 leads this result
ApprenticeBench
Not directly comparable
deepSwe
Not directly comparable
SWE-bench Verified
Not directly comparable
SWE-bench Pro
Grok 4.5 leads this result
SWE Multilingual
Claude Sonnet 5 leads this result
SWE Multimodal
Not directly comparable
Terminal-Bench 2.1
Grok 4.5 leads this result
FrontierCode 1.1 Main
Not directly comparable
CursorBench 3.2
Shared sourceGrok 4.5 leads this result
VulcanBench CII v1
Not directly comparable
LiveCodeBench (Vals)
Grok 4.5 leads this result
SWE-bench (Vals)
Grok 4.5 leads this result
CursorBench 4.0
Not directly comparable
VulcanBench v3
Not directly comparable
PostTrainBench v1.1
Not directly comparable
HLE
Not directly comparable
HLE w/o tools
Not directly comparable
HLE-Verified
Not directly comparable
LABBench2
Not directly comparable
GPQA Diamond (Vals)
Grok 4.5 leads this result
MMLU-Pro (Vals)
Grok 4.5 leads this result
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Last updated October 7, 2026
