Agentic
Like-for-like- GPT-5.6 Luna
- 56.8
- Supported · #32/152
- Inkling-Small
- 36.9
- Supported · #128/152
- Basis
- BenchAlign lane · 9 vs 5 public rows
- Reading
- GPT-5.6 Luna leads
GPT-5.6 Luna vs Inkling-Small
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
GPT-5.6 Luna has the higher public score estimate, 64.65 versus 59.25, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
12 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
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.
Coding work
Code generation, repair, and software-engineering tasks
GPT-5.6 Luna
GPT-5.6 Luna leads on the public coding lane, 66.8 to 43.8, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Agentic work
Tool use, computer use, and multi-step task completion
GPT-5.6 Luna
GPT-5.6 Luna leads on the public agentic lane, 56.8 to 36.9, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Long documents
Prompts that approach the documented context limit
GPT-5.6 Luna
GPT-5.6 Luna has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Chat turn cost
1K fresh input + 500 output tokens
GPT-5.6 Luna
GPT-5.6 Luna 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
GPT-5.6 Luna
GPT-5.6 Luna has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
GPT-5.6 Luna
GPT-5.6 Luna has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
18 GPT-5.6 Luna only
12 Shared
13 Inkling-Small only
- Shared results
- 12
- GPT-5.6 Luna only
- 18
- Inkling-Small only
- 13
- Like-for-like categories
- 3 / 8
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
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.
Coding
Like-for-like- GPT-5.6 Luna
- 66.8
- Supported · #9/151
- Inkling-Small
- 43.8
- Supported · #97/151
- Basis
- BenchAlign lane · 8 vs 6 public rows
- Reading
- GPT-5.6 Luna leads
Knowledge
Like-for-like- GPT-5.6 Luna
- 64.1
- Supported · #27/183
- Inkling-Small
- 56.5
- Supported · #46/183
- Basis
- BenchAlign lane · 6 vs 6 public rows
- Reading
- GPT-5.6 Luna leads · intervals overlap
Multimodal
Directional only- GPT-5.6 Luna
- 67.1
- #21/48
- Inkling-Small
- 48.8
- #39/48
- Basis
- Provisional lane · 1 vs 2 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- GPT-5.6 Luna
- 51.2
- #19/20
- Inkling-Small
- 42.7
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 2 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- GPT-5.6 Luna
- 94.4
- Unranked · 3 rankable rows
- Inkling-Small
- 76.9
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-5.6 Luna
- Not ranked
- Inkling-Small
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-5.6 Luna
- Not ranked
- Inkling-Small
- 89.6
- #25/123
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | GPT-5.6 Luna | Inkling-Small | Basis | Reading |
|---|---|---|---|---|
| Agentic | 56.8Supported · #32/152 | 36.9Supported · #128/152 | Like-for-likeBenchAlign lane · 9 vs 5 public rows | GPT-5.6 Luna leads |
| Coding | 66.8Supported · #9/151 | 43.8Supported · #97/151 | Like-for-likeBenchAlign lane · 8 vs 6 public rows | GPT-5.6 Luna leads |
| Knowledge | 64.1Supported · #27/183 | 56.5Supported · #46/183 | Like-for-likeBenchAlign lane · 6 vs 6 public rows | GPT-5.6 Luna leads · intervals overlap |
| Multimodal | 67.1#21/48 | 48.8#39/48 | Directional onlyProvisional lane · 1 vs 2 weighted rows | Directional only |
| Reasoning | 51.2#19/20 | 42.7Unranked · 3 rankable rows | Not comparableProvisional lane · 2 vs 1 weighted rows | Not comparable |
| Math | 94.4Unranked · 3 rankable rows | 76.9Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 89.6#25/123 | Not comparableProvisional lane · 0 vs 1 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.
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.
Terminal-Bench 2.0
Agentic
ARC-AGI-2
Reasoning
SWE-bench Pro
Coding
BrowseComp
Agentic
MMMU-Pro
Multimodal
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
- GPT-5.6 Luna
- $0.0008
- Fits in one request
- Inkling-Small
- $0.0013
- Fits in one request
GPT-5.6 Luna has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- GPT-5.6 Luna
- $0.0136
- Fits in one request
- Inkling-Small
- $0.03332
- Fits in one request
GPT-5.6 Luna has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-5.6 Luna
- $0.02
- Fits in one request
- Inkling-Small
- $0.0492
- Fits in one request
GPT-5.6 Luna 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.
SpecificationGPT-5.6 LunaInkling-Small
Context window
Maximum documented context; output-token limits may be lower.
GPT-5.6 Luna
1.05M
OpenAI model catalogInkling-Small
1M
API model ID
GPT-5.6 Luna
gpt-5.6-luna
OpenAI model catalogInkling-Small
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-5.6 Luna
$0.02 per 1M cached input tokens
OpenAI pricingInkling-Small
$0.116 per 1M cached input tokens
Documented inputs
GPT-5.6 Luna
text, image
OpenAI model catalogInkling-Small
Not sourced
Documented outputs
GPT-5.6 Luna
Inkling-Small
Not sourced
Provider availability
GPT-5.6 Luna
Generally Available · OpenAI Responses API
OpenAI model catalogInkling-Small
Not sourced
Reasoning profile
GPT-5.6 Luna
Reasoning
Inkling-Small
Hybrid
Weight access
GPT-5.6 Luna
Proprietary
Inkling-Small
Open Weight
License
GPT-5.6 Luna
Proprietary
Inkling-Small
Open Weight
Release date
GPT-5.6 Luna
2026-07-09
Inkling-Small
2026-07-30
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
- GPT-5.6 Luna has the higher public score estimate, 64.65 versus 59.25, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.0136 vs $0.03332. Cache-heavy agent loop: $0.02 vs $0.0492.
- Context tradeoff
- GPT-5.6 Luna has the larger documented window (1.05M).
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 evidence43 rows
Agentic
Terminal-Bench 3.0
GPT-5.6 Luna14.3%SourceInkling-Small—Not directly comparable
Terminal-Bench 2.0
GPT-5.6 Luna84.7%SourceInkling-Small64.7%SourceGPT-5.6 Luna leads this result
BrowseComp
GPT-5.6 Luna83.3%SourceInkling-Small77.4%SourceGPT-5.6 Luna leads this result
OSWorld 2.0
GPT-5.6 Luna45.6%SourceInkling-Small—Not directly comparable
CyberGym
GPT-5.6 Luna77.9%SourceInkling-Small—Not directly comparable
ExploitGym
GPT-5.6 Luna12.4%SourceInkling-Small—Not directly comparable
Toolathlon
GPT-5.6 Luna53.4%SourceInkling-Small—Not directly comparable
Terminal-Bench 2.1 (Vals)
GPT-5.6 Luna79.0%SourceInkling-Small55.1%SourceGPT-5.6 Luna leads this result
ApprenticeBench
GPT-5.6 Luna7%SourceInkling-Small—Not directly comparable
MCP Atlas
GPT-5.6 Luna—Inkling-Small79.6%SourceNot directly comparable
Toolathlon-Verified
GPT-5.6 Luna—Inkling-Small54.4%SourceNot directly comparable
Coding
SWE-bench Pro
GPT-5.6 Luna62.7%SourceInkling-Small55.9%SourceGPT-5.6 Luna leads this result
Terminal-Bench 2.0
GPT-5.6 Luna84.7%SourceInkling-Small64.7%SourceGPT-5.6 Luna leads this result
DeepSWE
GPT-5.6 Luna67.2%SourceInkling-Small—Not directly comparable
FrontierCode 1.1 Extended
GPT-5.6 Luna55.1%SourceInkling-Small—Not directly comparable
cursorBench32
GPT-5.6 Luna61.1%SourceInkling-Small—Not directly comparable
VulcanBench v3
GPT-5.6 Luna85.5%SourceInkling-Small—Not directly comparable
SWE-bench (Vals)
GPT-5.6 Luna93.0%SourceInkling-Small82.2%SourceGPT-5.6 Luna leads this result
cursorBench40
GPT-5.6 Luna35.9%SourceInkling-Small—Not directly comparable
SWE-bench Verified
GPT-5.6 Luna—Inkling-Small80.2%SourceNot directly comparable
SciCode
GPT-5.6 Luna—Inkling-Small48.7%SourceNot directly comparable
LiveCodeBench (Vals)
GPT-5.6 Luna—Inkling-Small85.9%SourceNot directly comparable
Reasoning
Knowledge
GPQA
GPT-5.6 Luna92.3%SourceInkling-Small89.5%SourceGPT-5.6 Luna leads this result
GPQA-D
GPT-5.6 Luna92.3%SourceInkling-Small89.5%SourceGPT-5.6 Luna leads this result
HealthBench Professional
GPT-5.6 Luna55.7%SourceInkling-Small—Not directly comparable
HealthBench Hard
GPT-5.6 Luna32.0%SourceInkling-Small—Not directly comparable
GPQA Diamond (Vals)
GPT-5.6 Luna91.7%SourceInkling-Small83.6%SourceGPT-5.6 Luna leads this result
MMLU-Pro (Vals)
GPT-5.6 Luna86.0%SourceInkling-Small85.6%SourceGPT-5.6 Luna leads this result
HLE
GPT-5.6 Luna—Inkling-Small47.8%SourceNot directly comparable
HLE w/o tools
GPT-5.6 Luna—Inkling-Small31.6%SourceNot directly comparable
Math
FrontierMath (legacy)
GPT-5.6 Luna78.6%SourceInkling-Small—Not directly comparable
FrontierMath v2 (Tiers 1-3)
GPT-5.6 Luna78.600%SourceInkling-Small—Not directly comparable
FrontierMath v2 (Tier 4)
GPT-5.6 Luna58.500%SourceInkling-Small—Not directly comparable
AIME26
GPT-5.6 Luna—Inkling-Small95.5%SourceNot directly comparable
HMMT Feb 2026
GPT-5.6 Luna—Inkling-Small90.2%SourceNot directly comparable
Multimodal
MMMU-Pro
GPT-5.6 Luna78.4%SourceInkling-Small74%SourceGPT-5.6 Luna leads this result
MMMU-Pro w/ Python
GPT-5.6 Luna79.5%SourceInkling-Small—Not directly comparable
CharXiv
GPT-5.6 Luna—Inkling-Small81.3%SourceNot directly comparable
CharXiv w/o tools
GPT-5.6 Luna—Inkling-Small77.4%SourceNot directly comparable
Instruction following
IFBench
GPT-5.6 Luna—Inkling-Small82.2%SourceNot directly comparable
Frequently asked questions
Which is better, GPT-5.6 Luna or Inkling-Small?
GPT-5.6 Luna has the higher public score estimate, 64.65 versus 59.25, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, GPT-5.6 Luna or Inkling-Small?
GPT-5.6 Luna leads the public coding lane, 66.8 to 43.8, with Supported evidence for both models and non-overlapping 90% intervals.
Which is better for agentic tasks, GPT-5.6 Luna or Inkling-Small?
GPT-5.6 Luna leads the public agentic tasks lane, 56.8 to 36.9, with Supported evidence for both models and non-overlapping 90% intervals.
Which costs less, GPT-5.6 Luna or Inkling-Small?
For the stated presets, chat costs $0.0008 on GPT-5.6 Luna and $0.0013 on Inkling-Small; repository review costs $0.0136 and $0.03332; the cache-heavy agent loop costs $0.02 and $0.0492. Costs use the listed standard API rates.
Which has the larger context window, GPT-5.6 Luna or Inkling-Small?
GPT-5.6 Luna has the larger documented context window: 1.05M, compared with 1M.
Related comparisons
Last updated September 10, 2026
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