Agentic
Like-for-like- Claude Sonnet 5
- 65.9
- Supported · #11/153
- Grok 4.20
- 26.7
- Supported · #146/153
- Basis
- BenchAlign lane · 7 vs 4 public rows
- Reading
- Claude Sonnet 5 leads
Keep up with the models you depend on. Follow price changes, retirements, and API updates.Follow the models you depend on.
Follow model changesUpdated September 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Sonnet 5 has the higher public score estimate, 69.92 versus 67.21, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
10 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
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 leads on the public coding lane, 64.1 to 28.3, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Tool use, computer use, and multi-step task completion
Claude Sonnet 5
Claude Sonnet 5 leads on the public agentic lane, 65.9 to 26.7, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Prompts that approach the documented context limit
Grok 4.20
Grok 4.20 has the larger documented context window.
Confidence: documented
1K fresh input + 500 output tokens
Grok 4.20
Grok 4.20 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
200K cached + 20K fresh input + 10K output tokens
Claude Sonnet 5
Claude Sonnet 5 has the lower estimated token cost for this stated workload. Grok 4.20 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
50K fresh input + 3K output tokens
Grok 4.20
Grok 4.20 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
| Category | Claude Sonnet 5 | Grok 4.20 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 65.9Supported · #11/153 | 26.7Supported · #146/153 | Like-for-likeBenchAlign lane · 7 vs 4 public rows | Claude Sonnet 5 leads |
| Coding | 64.1Supported · #13/152 | 28.3Supported · #142/152 | Like-for-likeBenchAlign lane · 11 vs 6 public rows | Claude Sonnet 5 leads |
| Knowledge | 66.6Supported · #20/183 | 49.3Supported · #85/183 | Like-for-likeBenchAlign lane · 6 vs 6 public rows | Claude Sonnet 5 leads · intervals overlap |
| Multimodal | 77.5#13/48 | 34.6#43/48 | Directional onlyProvisional lane · 1 vs 2 weighted rows | Directional only |
| Reasoning | 77.4Unranked · 2 rankable rows | 34.2Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 2 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 |
| Instruction following | 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) 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.
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
CharXiv
Multimodal
HLE w/o tools
Knowledge
SWE-bench Pro
Coding
SWE-bench Verified
Coding
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 4.20 has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Grok 4.20 has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Claude Sonnet 5 has the lower modeled cost
Grok 4.20 has no published cached-input rate, so cached tokens use its listed input rate.
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 4.20
2M
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewGrok 4.20
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 4.20
Not published
Claude Sonnet 5
text, image
Anthropic model overviewGrok 4.20
Not sourced
Claude Sonnet 5
Grok 4.20
Not sourced
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewGrok 4.20
Not sourced
Claude Sonnet 5
Reasoning
Grok 4.20
Reasoning
Claude Sonnet 5
Proprietary
Grok 4.20
Proprietary
Claude Sonnet 5
Proprietary
Grok 4.20
Proprietary
Claude Sonnet 5
2026-06-30
Grok 4.20
2026-03-10
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 3.0
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 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
DeepSearchQA
Not directly comparable
Gert Labs
Not directly comparable
SWE-bench Verified
Claude Sonnet 5 leads this result
SWE-bench Pro
Claude Sonnet 5 leads this result
SWE Multilingual
Not directly comparable
SWE Multimodal
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
FrontierCode 1.1 Main
Not directly comparable
cursorBench32
Not directly comparable
VulcanBench CII v1
Not directly comparable
LiveCodeBench (Vals)
Grok 4.20 leads this result
SWE-bench (Vals)
Claude Sonnet 5 leads this result
cursorBench40
Not directly comparable
LiveCodeBench Pro
Not directly comparable
Vibe Code Bench
Not directly comparable
HLE
Not directly comparable
HLE w/o tools
Claude Sonnet 5 leads this result
HLE-Verified
Not directly comparable
LABBench2
Not directly comparable
GPQA Diamond (Vals)
Claude Sonnet 5 leads this result
MMLU-Pro (Vals)
Claude Sonnet 5 leads this result
GPQA-D
Not directly comparable
HealthBench Hard
Not directly comparable
MedXpertQA (Text)
Not directly comparable
CharXiv
Claude Sonnet 5 leads this result
CharXiv w/o tools
Not directly comparable
MMMU-Pro
Not directly comparable
ERQA
Not directly comparable
SimpleVQA
Not directly comparable
MedXpertQA (MM)
Not directly comparable
Claude Sonnet 5 has the higher public score estimate, 69.92 versus 67.21, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Claude Sonnet 5 leads the public coding lane, 64.1 to 28.3, with Supported evidence for both models and non-overlapping 90% intervals.
Claude Sonnet 5 leads the public agentic tasks lane, 65.9 to 26.7, with Supported evidence for both models and non-overlapping 90% intervals.
For the stated presets, chat costs $0.007 on Claude Sonnet 5 and $0.005 on Grok 4.20; repository review costs $0.13 and $0.118; the cache-heavy agent loop costs $0.18 and $0.5. Grok 4.20 has no published cached-input rate, so cached tokens use its listed input rate.
Grok 4.20 has the larger documented context window: 2M, compared with 1M.
Last updated September 14, 2026
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.