Model A

OpenAI

80.63/100

Supported · Public rank #6

90% interval 77.5–83.7

GPT-5.6 Sol vs Inkling-Small

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

Inkling-Small

Thinking Machines Lab

59.25/100

Supported · Public rank #69

90% interval 52.4–66.1

Decision reading

GPT-5.6 Sol has the higher public score, 80.63 versus 59.25, and the 90% score intervals do not overlap.

13 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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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 Sol
GPT-5.6 Sol leads on the public coding lane, 74.5 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 Sol
GPT-5.6 Sol leads on the public agentic lane, 70.1 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 Sol
GPT-5.6 Sol has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Chat turn cost
1K fresh input + 500 output tokens
Inkling-Small
Inkling-Small 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
Inkling-Small
Inkling-Small 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
Inkling-Small
Inkling-Small 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.

24 GPT-5.6 Sol only

13 Shared

12 Inkling-Small only

Shared results: 13
GPT-5.6 Sol only: 24
Inkling-Small only: 12
Like-for-like categories: 3 / 8

2 categories rest 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.

Agentic

Like-for-like

GPT-5.6 Sol: 70.1; Supported · #6/152
Inkling-Small: 36.9; Supported · #128/152
Basis: BenchAlign lane · 9 vs 5 public rows
Reading: GPT-5.6 Sol leads

Coding

Like-for-like

GPT-5.6 Sol: 74.5; Supported · #5/151
Inkling-Small: 43.8; Supported · #97/151
Basis: BenchAlign lane · 12 vs 6 public rows
Reading: GPT-5.6 Sol leads

Knowledge

Like-for-like

GPT-5.6 Sol: 80.5; Supported · #5/183
Inkling-Small: 56.5; Supported · #46/183
Basis: BenchAlign lane · 8 vs 6 public rows
Reading: GPT-5.6 Sol leads

Multimodal

Directional only

GPT-5.6 Sol: 87.5; #4/48
Inkling-Small: 48.8; #39/48
Basis: Provisional lane · 1 vs 2 weighted rows
Reading: Directional only

Instruction following

Directional only

GPT-5.6 Sol: 89.1; #27/123
Inkling-Small: 89.6; #25/123
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Directional only

Reasoning

Not comparable

GPT-5.6 Sol: 70.4; #12/20
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 Sol: 97.0; 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 Sol: Not ranked
Inkling-Small: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for GPT-5.6 Sol and Inkling-Small
Category	GPT-5.6 Sol	Inkling-Small	Basis	Reading
Agentic	70.1Supported · #6/152	36.9Supported · #128/152	Like-for-likeBenchAlign lane · 9 vs 5 public rows	GPT-5.6 Sol leads
Coding	74.5Supported · #5/151	43.8Supported · #97/151	Like-for-likeBenchAlign lane · 12 vs 6 public rows	GPT-5.6 Sol leads
Knowledge	80.5Supported · #5/183	56.5Supported · #46/183	Like-for-likeBenchAlign lane · 8 vs 6 public rows	GPT-5.6 Sol leads
Multimodal	87.5#4/48	48.8#39/48	Directional onlyProvisional lane · 1 vs 2 weighted rows	Directional only
Instruction following	89.1#27/123	89.6#25/123	Directional onlyProvisional lane · 0 vs 1 weighted rows	Directional only
Reasoning	70.4#12/20	42.7Unranked · 3 rankable rows	Not comparableProvisional lane · 2 vs 1 weighted rows	Not comparable
Math	97.0Unranked · 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

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.

ARC-AGI-2
Reasoning
GPT-5.6 Sol: 92.5%Inkling-Small: 40.1%Normalized gap 52.4GPT-5.6 Sol source Inkling-Small source
Terminal-Bench 2.0
Agentic
GPT-5.6 Sol: 91.9%Inkling-Small: 64.7%Normalized gap 27.2GPT-5.6 Sol source Inkling-Small source
BrowseComp
Agentic
GPT-5.6 Sol: 92.2%Inkling-Small: 77.4%Normalized gap 14.8GPT-5.6 Sol source Inkling-Small source
MMMU-Pro
Multimodal
GPT-5.6 Sol: 83%Inkling-Small: 74%Normalized gap 9.0GPT-5.6 Sol source Inkling-Small source
SWE-bench Pro
Coding
GPT-5.6 Sol: 64.6%Inkling-Small: 55.9%Normalized gap 8.7GPT-5.6 Sol source Inkling-Small source

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 Sol: $0.014; Fits in one request
Inkling-Small: $0.0013; Fits in one request

Inkling-Small has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

GPT-5.6 Sol: $0.26; Fits in one request
Inkling-Small: $0.03332; Fits in one request

Inkling-Small 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 Sol: $0.36; Fits in one request
Inkling-Small: $0.0492; Fits in one request

Inkling-Small 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 SolInkling-Small

Context window

Maximum documented context; output-token limits may be lower.

GPT-5.6 Sol

1.05M

OpenAI model catalog

Inkling-Small

API model ID

GPT-5.6 Sol

gpt-5.6-sol

OpenAI model catalog

Inkling-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 Sol

$0.4 per 1M cached input tokens

OpenAI pricing

Inkling-Small

$0.116 per 1M cached input tokens

Documented inputs

GPT-5.6 Sol

text, image

OpenAI model catalog

Inkling-Small

Not sourced

Documented outputs

GPT-5.6 Sol

text

OpenAI model catalog

Inkling-Small

Not sourced

Provider availability

GPT-5.6 Sol

Generally Available · OpenAI Responses API

OpenAI model catalog

Inkling-Small

Not sourced

Reasoning profile

GPT-5.6 Sol

Reasoning

Inkling-Small

Hybrid

Weight access

GPT-5.6 Sol

Proprietary

Inkling-Small

Open Weight

License

GPT-5.6 Sol

Proprietary

Inkling-Small

Open Weight

Release date

GPT-5.6 Sol

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 Sol has the higher public score, 80.63 versus 59.25, and the 90% score intervals do not overlap.
Workload cost: Repository review: $0.26 vs $0.03332. Cache-heavy agent loop: $0.36 vs $0.0492.
Context tradeoff: GPT-5.6 Sol 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 evidence49 rows

Agentic

Terminal-Bench 3.0
GPT-5.6 Sol34.6%
Source
Inkling-Small—
Not directly comparable
Terminal-Bench 2.0
GPT-5.6 Sol91.9%
Source
Inkling-Small64.7%
Source
GPT-5.6 Sol leads this result
BrowseComp
GPT-5.6 Sol92.2%
Source
Inkling-Small77.4%
Source
GPT-5.6 Sol leads this result
OSWorld 2.0
GPT-5.6 Sol62.6%
Source
Inkling-Small—
Not directly comparable
CyberGym
GPT-5.6 Sol84.5%
Source
Inkling-Small—
Not directly comparable
ExploitGym
GPT-5.6 Sol33.7%
Source
Inkling-Small—
Not directly comparable
Toolathlon
GPT-5.6 Sol58%
Source
Inkling-Small—
Not directly comparable
Terminal-Bench 2.1 (Vals)
GPT-5.6 Sol85.8%
Source
Inkling-Small55.1%
Source
GPT-5.6 Sol leads this result
ApprenticeBench
GPT-5.6 Sol26%
Source
Inkling-Small—
Not directly comparable
MCP Atlas
GPT-5.6 Sol—
Inkling-Small79.6%
Source
Not directly comparable
Toolathlon-Verified
GPT-5.6 Sol—
Inkling-Small54.4%
Source
Not directly comparable

Coding

Bug Hunt Bench
GPT-5.6 Sol42 fixes
Source
Inkling-Small—
Not directly comparable
SWE-bench Pro
GPT-5.6 Sol64.6%
Source
Inkling-Small55.9%
Source
GPT-5.6 Sol leads this result
Terminal-Bench 2.0
GPT-5.6 Sol91.9%
Source
Inkling-Small64.7%
Source
GPT-5.6 Sol leads this result
DeepSWE
GPT-5.6 Sol72.7%
Source
Inkling-Small—
Not directly comparable
FrontierCode 1.1 Extended
GPT-5.6 Sol60.6%
Source
Inkling-Small—
Not directly comparable
FrontierSWE v2
GPT-5.6 Sol32.2%
Source
Inkling-Small—
Not directly comparable
cursorBench32
GPT-5.6 Sol67.2%
Source
Inkling-Small—
Not directly comparable
VulcanBench v3
GPT-5.6 Sol87.0%
Source
Inkling-Small—
Not directly comparable
VulcanBench CII v1
GPT-5.6 Sol86.5%
Source
Inkling-Small—
Not directly comparable
LiveCodeBench (Vals)
GPT-5.6 Sol82.6%
Source
Inkling-Small85.9%
Source
Inkling-Small leads this result
SWE-bench (Vals)
GPT-5.6 Sol96.2%
Source
Inkling-Small82.2%
Source
GPT-5.6 Sol leads this result
cursorBench40
GPT-5.6 Sol41.7%
Source
Inkling-Small—
Not directly comparable
SWE-bench Verified
GPT-5.6 Sol—
Inkling-Small80.2%
Source
Not directly comparable
SciCode
GPT-5.6 Sol—
Inkling-Small48.7%
Source
Not directly comparable

Reasoning

ARC-AGI-2
GPT-5.6 Sol92.5%
Source
Inkling-Small40.1%
Source
GPT-5.6 Sol leads this result
ARC-AGI-3
GPT-5.6 Sol7.8%
Source
Inkling-Small—
Not directly comparable
GeneBench-Pro
GPT-5.6 Sol28.7%
Source
Inkling-Small—
Not directly comparable
CritPt
GPT-5.6 Sol—
Inkling-Small8.3%
Source
Not directly comparable

Knowledge

GPQA
GPT-5.6 Sol94.6%
Source
Inkling-Small89.5%
Source
GPT-5.6 Sol leads this result
GPQA-D
GPT-5.6 Sol94.6%
Source
Inkling-Small89.5%
Source
GPT-5.6 Sol leads this result
HLE-Verified
GPT-5.6 Sol54.5%
Source
Inkling-Small—
Not directly comparable
LABBench2
GPT-5.6 Sol82.1%
Source
Inkling-Small—
Not directly comparable
HealthBench Professional
GPT-5.6 Sol60.5%
Source
Inkling-Small—
Not directly comparable
HealthBench Hard
GPT-5.6 Sol33.1%
Source
Inkling-Small—
Not directly comparable
GPQA Diamond (Vals)
GPT-5.6 Sol95.2%
Source
Inkling-Small83.6%
Source
GPT-5.6 Sol leads this result
MMLU-Pro (Vals)
GPT-5.6 Sol89.1%
Source
Inkling-Small85.6%
Source
GPT-5.6 Sol leads this result
HLE
GPT-5.6 Sol—
Inkling-Small47.8%
Source
Not directly comparable
HLE w/o tools
GPT-5.6 Sol—
Inkling-Small31.6%
Source
Not directly comparable

Math

FrontierMath (legacy)
GPT-5.6 Sol89%
Source
Inkling-Small—
Not directly comparable
FrontierMath v2 (Tiers 1-3)
GPT-5.6 Sol89.000%
Source
Inkling-Small—
Not directly comparable
FrontierMath v2 (Tier 4)
GPT-5.6 Sol83.000%
Source
Inkling-Small—
Not directly comparable
AIME26
GPT-5.6 Sol—
Inkling-Small95.5%
Source
Not directly comparable
HMMT Feb 2026
GPT-5.6 Sol—
Inkling-Small90.2%
Source
Not directly comparable

Multimodal

MMMU-Pro
GPT-5.6 Sol83%
Source
Inkling-Small74%
Source
GPT-5.6 Sol leads this result
MMMU-Pro w/ Python
GPT-5.6 Sol84.6%
Source
Inkling-Small—
Not directly comparable
CharXiv
GPT-5.6 Sol—
Inkling-Small81.3%
Source
Not directly comparable
CharXiv w/o tools
GPT-5.6 Sol—
Inkling-Small77.4%
Source
Not directly comparable

Instruction following

IFBench
GPT-5.6 Sol—
Inkling-Small82.2%
Source
Not directly comparable

Frequently asked questions

Which is better, GPT-5.6 Sol or Inkling-Small?

GPT-5.6 Sol has the higher public score, 80.63 versus 59.25, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, GPT-5.6 Sol or Inkling-Small?

GPT-5.6 Sol leads the public coding lane, 74.5 to 43.8, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, GPT-5.6 Sol or Inkling-Small?

GPT-5.6 Sol leads the public agentic tasks lane, 70.1 to 36.9, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, GPT-5.6 Sol or Inkling-Small?

For the stated presets, chat costs $0.014 on GPT-5.6 Sol and $0.0013 on Inkling-Small; repository review costs $0.26 and $0.03332; the cache-heavy agent loop costs $0.36 and $0.0492. Costs use the listed standard API rates.

Which has the larger context window, GPT-5.6 Sol or Inkling-Small?

GPT-5.6 Sol has the larger documented context window: 1.05M, compared with 1M.

Related comparisons

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Last updated September 10, 2026

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GPT-5.6 Sol vs Inkling-Small

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Knowledge

Multimodal

Instruction following

Reasoning

Math

Multilingual

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multimodal

Instruction following

Frequently asked questions

Which is better, GPT-5.6 Sol or Inkling-Small?

Which is better for coding, GPT-5.6 Sol or Inkling-Small?

Which is better for agentic tasks, GPT-5.6 Sol or Inkling-Small?

Which costs less, GPT-5.6 Sol or Inkling-Small?

Which has the larger context window, GPT-5.6 Sol or Inkling-Small?

Related comparisons

Watch GPT-5.6 Sol vs Inkling-Small