Coding work
Code generation, repair, and software-engineering tasks
Grok 4.6
Grok 4.6 leads on the public coding lane, 62 to 48.1, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Claude Sonnet 4.6 vs Grok 4.6
Updated September 25, 2026. Rank says Grok 4.6 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
Grok 4.6 has the higher public score estimate, 69.19 versus 56.35, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 6
- Claude Sonnet 4.6 only
- 20
- Grok 4.6 only
- 11
- Like-for-like categories
- 3 / 8
Supported: Claude Sonnet 4.6 and Grok 4.6How 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
Grok 4.6
Grok 4.6 leads on the public agentic lane, 67.9 to 41.8, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: strongerLong documents
Prompts that approach the documented context limit
Grok 4.6
Grok 4.6 has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Chat turn cost
1K fresh input + 500 output tokens
Grok 4.6
Grok 4.6 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
Grok 4.6
Grok 4.6 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
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
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.
48.1Claude Sonnet 4.662.0Grok 4.6
Like-for-like · BenchAlign v5.7
Grok 4.6 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.
20 Claude Sonnet 4.6 only
6 Shared
11 Grok 4.6 only
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.
LiveCodeBench (Vals)Coding
Normalized gap 6.1Claude Sonnet 4.6:82.1%Grok 4.6:88.2%MMLU-Pro (Vals)Knowledge
Normalized gap 2.1Claude Sonnet 4.6:87.3%Grok 4.6:89.4%
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 Sonnet 4.6
- 41.8
- Supported · #44/105
- Grok 4.6
- 67.9
- Supported · #8/105
- Basis
- BenchAlign v5.7 lane · 9 vs 4 public rows
- Reading
- Grok 4.6 leads
Coding
Like-for-like- Claude Sonnet 4.6
- 48.1
- Supported · #41/135
- Grok 4.6
- 62.0
- Supported · #14/135
- Basis
- BenchAlign v5.7 lane · 8 vs 8 public rows
- Reading
- Grok 4.6 leads · intervals overlap
Knowledge
Like-for-like- Claude Sonnet 4.6
- 53.0
- Supported · #48/158
- Grok 4.6
- 69.0
- Supported · #13/158
- Basis
- BenchAlign v5.7 lane · 6 vs 2 public rows
- Reading
- Grok 4.6 leads · intervals overlap
Reasoning
Not comparable- Claude Sonnet 4.6
- 69.0
- Unranked · 2 rankable rows
- Grok 4.6
- 57.6
- #16/19
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Sonnet 4.6
- 54.1
- #35/50
- Grok 4.6
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 4.6
- Not ranked
- Grok 4.6
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 4.6
- 46.6
- #88/124
- Grok 4.6
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 4.6
- 48.8
- Unranked · 2 rankable rows
- Grok 4.6
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Sonnet 4.6 | Grok 4.6 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 41.8Supported · #44/105 | 67.9Supported · #8/105 | Like-for-likeBenchAlign v5.7 lane · 9 vs 4 public rows | Grok 4.6 leads |
| Coding | 48.1Supported · #41/135 | 62.0Supported · #14/135 | Like-for-likeBenchAlign v5.7 lane · 8 vs 8 public rows | Grok 4.6 leads · intervals overlap |
| Knowledge | 53.0Supported · #48/158 | 69.0Supported · #13/158 | Like-for-likeBenchAlign v5.7 lane · 6 vs 2 public rows | Grok 4.6 leads · intervals overlap |
| Reasoning | 69.0Unranked · 2 rankable rows | 57.6#16/19 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Multimodal | 54.1#35/50 | Not ranked | 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 | 46.6#88/124 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 48.8Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) 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 Sonnet 4.6
- $0.0105
- Fits in one request
- Grok 4.6
- $0.005
- Fits in one request
Grok 4.6 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Sonnet 4.6
- $0.195
- Fits in one request
- Grok 4.6
- $0.118
- Fits in one request
Grok 4.6 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 Sonnet 4.6
- $0.81
- Does not fit in one request
- Cached input priced at the published list-input rate
- Grok 4.6
- $0.2
- Fits in one request
Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
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 Sonnet 4.6Grok 4.6
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 4.6
200K
Grok 4.6
API model ID
Claude Sonnet 4.6
Not sourced
Grok 4.6
grok-4.6
xAI Grok 4.6 release notesCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 4.6
Not published
Grok 4.6
$0.5 per 1M cached input tokens
xAI Grok 4.6 release notesDocumented inputs
Claude Sonnet 4.6
Not sourced
Grok 4.6
Not sourced
Documented outputs
Claude Sonnet 4.6
Not sourced
Grok 4.6
Not sourced
Provider availability
Claude Sonnet 4.6
Not sourced
Grok 4.6
Not sourced
Reasoning profile
Claude Sonnet 4.6
Non-Reasoning
Grok 4.6
Reasoning
Weight access
Claude Sonnet 4.6
Proprietary
Grok 4.6
Proprietary
License
Claude Sonnet 4.6
Proprietary
Grok 4.6
Proprietary
Release date
Claude Sonnet 4.6
2026-02-01
Grok 4.6
2026-08-12
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
- Grok 4.6 has the higher public score estimate, 69.19 versus 56.35, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.195 vs $0.118. Cache-heavy agent loop: $0.81 vs $0.2.
- Context tradeoff
- Grok 4.6 has the larger documented window (500K).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Sonnet 4.6 or Grok 4.6?
Grok 4.6 has the higher public score estimate, 69.19 versus 56.35, 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 Sonnet 4.6 or Grok 4.6?
Grok 4.6 leads the public coding lane, 62 to 48.1, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Claude Sonnet 4.6 or Grok 4.6?
Grok 4.6 leads the public agentic tasks lane, 67.9 to 41.8, with Supported evidence for both models and non-overlapping 90% intervals.
Which costs less, Claude Sonnet 4.6 or Grok 4.6?
For the stated presets, chat costs $0.0105 on Claude Sonnet 4.6 and $0.005 on Grok 4.6; repository review costs $0.195 and $0.118; the cache-heavy agent loop costs $0.81 and $0.2. Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Sonnet 4.6 or Grok 4.6?
Grok 4.6 has the larger documented context window: 500K, compared with 200K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence37 rows
Agentic
Terminal-Bench 2.0
Claude Sonnet 4.659.1%SourceGrok 4.6—Not directly comparable
OSWorld-Verified
Claude Sonnet 4.672.1%SourceGrok 4.6—Not directly comparable
Claw-Eval
Claude Sonnet 4.667.8%SourceGrok 4.6—Not directly comparable
CyberGym
Claude Sonnet 4.665.2%SourceGrok 4.6—Not directly comparable
Gert Labs
Claude Sonnet 4.662.92%SourceGrok 4.6—Not directly comparable
OSWorld 2.0
Claude Sonnet 4.68.3%SourceGrok 4.6—Not directly comparable
JobBench
Claude Sonnet 4.636.9%SourceGrok 4.6—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Sonnet 4.657.3%SourceGrok 4.678.3%SourceGrok 4.6 leads this result
ApprenticeBench
Shared sourceClaude Sonnet 4.62%Grok 4.613%Grok 4.6 leads this result
Terminal-Bench 3.0
Claude Sonnet 4.6—Grok 4.626.5%SourceNot directly comparable
APEX-Agents
Claude Sonnet 4.6—Grok 4.657.5%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Sonnet 4.679.6%SourceGrok 4.6—Not directly comparable
SWE-Rebench
Claude Sonnet 4.660.7%SourceGrok 4.6—Not directly comparable
React Native Evals
Claude Sonnet 4.680.6%SourceGrok 4.6—Not directly comparable
Vibe Code Bench
Claude Sonnet 4.651.48%SourceGrok 4.6—Not directly comparable
cursorBench31
Claude Sonnet 4.648.8%SourceGrok 4.6—Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 4.624.3%SourceGrok 4.6—Not directly comparable
LiveCodeBench (Vals)
Claude Sonnet 4.682.1%SourceGrok 4.688.2%SourceGrok 4.6 leads this result
SWE-bench (Vals)
Claude Sonnet 4.677.4%SourceGrok 4.695.6%SourceGrok 4.6 leads this result
Bug Hunt Bench
Claude Sonnet 4.6—Grok 4.627 fixesSourceNot directly comparable
DeepSWE
Claude Sonnet 4.6—Grok 4.665.9%SourceNot directly comparable
cursorBench32
Claude Sonnet 4.6—Grok 4.670.8%SourceNot directly comparable
FrontierCode 1.1 Extended
Claude Sonnet 4.6—Grok 4.661.3%SourceNot directly comparable
VulcanBench v3
Claude Sonnet 4.6—Grok 4.687.0%SourceNot directly comparable
FrontierSWE v2
Claude Sonnet 4.6—Grok 4.625.3%SourceNot directly comparable
Reasoning
Multimodal
CharXiv
Claude Sonnet 4.677.4%SourceGrok 4.6—Not directly comparable
Knowledge
GPQA
Claude Sonnet 4.689.9%SourceGrok 4.6—Not directly comparable
SuperGPQA
Claude Sonnet 4.695%SourceGrok 4.6—Not directly comparable
MMLU-Pro
Claude Sonnet 4.679.2%SourceGrok 4.6—Not directly comparable
HLE
Claude Sonnet 4.649%SourceGrok 4.6—Not directly comparable
GPQA Diamond (Vals)
Claude Sonnet 4.685.6%SourceGrok 4.694.7%SourceGrok 4.6 leads this result
MMLU-Pro (Vals)
Claude Sonnet 4.687.3%SourceGrok 4.689.4%SourceGrok 4.6 leads this result
Math
37 public results · 6 shared
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Last updated September 25, 2026