Agentic
Not comparable- Grok 4.6
- Not measured
- Laguna S 2.1
- 70.2
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Model comparison
Grok 4.6 vs Laguna S 2.1
Updated August 12, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
1 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Long documents
Prompts that approach the documented context limit
Laguna S 2.1
Laguna S 2.1 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Laguna S 2.1
Laguna S 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Laguna S 2.1
Laguna S 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Laguna S 2.1
Laguna S 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
4 Grok 4.6 only
1 Shared
5 Laguna S 2.1 only
- Shared results
- 1
- Grok 4.6 only
- 4
- Laguna S 2.1 only
- 5
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Not comparable- Grok 4.6
- Not measured
- Laguna S 2.1
- 59.4
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Reasoning
Not comparable- Grok 4.6
- Not measured
- Laguna S 2.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Grok 4.6
- Not measured
- Laguna S 2.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Grok 4.6
- Not measured
- Laguna S 2.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Grok 4.6
- Not measured
- Laguna S 2.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Grok 4.6
- Not measured
- Laguna S 2.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Grok 4.6
- Not measured
- Laguna S 2.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Grok 4.6 | Laguna S 2.1 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | Not measured | 70.2 | Not comparable0 vs 1 rows | Not comparable |
| Coding | Not measured | 59.4 | Not comparable0 vs 1 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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
- Grok 4.6
- $0.005
- Fits in one request
- Laguna S 2.1
- $0.0002
- Fits in one request
Laguna S 2.1 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Grok 4.6
- $0.118
- Fits in one request
- Laguna S 2.1
- $0.0056
- Fits in one request
Laguna S 2.1 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Grok 4.6
- $0.2
- Fits in one request
- Laguna S 2.1
- $0.006
- Fits in one request
Laguna S 2.1 has the lower modeled cost
Costs use the listed standard API rates.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGrok 4.6Laguna S 2.1
Context window
Maximum documented context; output-token limits may be lower.
Grok 4.6
Laguna S 2.1
1M
API model ID
Grok 4.6
grok-4.6
xAI Grok 4.6 release notesLaguna S 2.1
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Grok 4.6
$0.5 per 1M cached input tokens
xAI Grok 4.6 release notesLaguna S 2.1
$0.01 per 1M cached input tokens
Documented inputs
Grok 4.6
Not sourced
Laguna S 2.1
Not sourced
Documented outputs
Grok 4.6
Not sourced
Laguna S 2.1
Not sourced
Provider availability
Grok 4.6
Not sourced
Laguna S 2.1
Not sourced
Reasoning profile
Grok 4.6
Reasoning
Laguna S 2.1
Reasoning
Weight access
Grok 4.6
Proprietary
Laguna S 2.1
Open Weight
License
Grok 4.6
Proprietary
Laguna S 2.1
Open Weight
Release date
Grok 4.6
2026-08-12
Laguna S 2.1
2026-07-21
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
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- Repository review: $0.118 vs $0.0056. Cache-heavy agent loop: $0.2 vs $0.006.
- Context tradeoff
- Laguna S 2.1 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 evidence10 rows
Agentic
Coding
deepSwe
Grok 4.665.9%SourceLaguna S 2.140.4%SourceGrok 4.6 leads this result
cursorBench32
Grok 4.669.9%SourceLaguna S 2.1—Not directly comparable
FrontierCode 1.1 Extended
Grok 4.661.3%SourceLaguna S 2.1—Not directly comparable
Terminal-Bench 2.0
Grok 4.6—Laguna S 2.170.2%SourceNot directly comparable
SWE Multilingual
Grok 4.6—Laguna S 2.178.5%SourceNot directly comparable
SWE-bench Pro
Grok 4.6—Laguna S 2.159.4%SourceNot directly comparable
Frequently asked questions
Which is better, Grok 4.6 or Laguna S 2.1?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Grok 4.6 or Laguna S 2.1?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Grok 4.6 or Laguna S 2.1?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Grok 4.6 or Laguna S 2.1?
For the stated presets, chat costs $0.005 on Grok 4.6 and $0.0002 on Laguna S 2.1; repository review costs $0.118 and $0.0056; the cache-heavy agent loop costs $0.2 and $0.006. Costs use the listed standard API rates.
Which has the larger context window, Grok 4.6 or Laguna S 2.1?
Laguna S 2.1 has the larger documented context window: 1M, compared with 500K.
Related comparisons
Last updated August 12, 2026
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