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GPT-5.6 Sol vs Inkling-Small

Updated October 29, 2026. Rank says GPT-5.6 Sol is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

GPT-5.6 Sol has the higher public score, 74.83 versus 49.5, and the 90% score intervals do not overlap. 16 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
OpenAI logo

OpenAI

74.83/100

Supported · Public rank #12

90% interval 71.8–77.9

Model B
Thinking Machines Lab logo

Thinking Machines Lab

49.5/100

Supported · Public rank #96

90% interval 32.4–66.6

Shared results
16
GPT-5.6 Sol only
28
Inkling-Small only
12
Like-for-like categories
3 / 8
Supported: GPT-5.6 Sol and Inkling-SmallHow 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    GPT-5.6 Sol

    GPT-5.6 Sol has the higher public coding point estimate, 67.1 to 36.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
  • Agentic work

    Tool use, computer use, and multi-step task completion

    GPT-5.6 Sol

    GPT-5.6 Sol has the higher public agentic point estimate, 68.8 to 36.1, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
  • 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

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.

67.1GPT-5.6 Sol36.9Inkling-Small

Like-for-like · BenchAlign v5.8

GPT-5.6 Sol has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

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.

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

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 v5.8 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
68.8
Supported · #13/135
Inkling-Small
36.1
Supported · #86/135
Basis
BenchAlign v5.8 lane · 10 vs 5 public rows
Reading
GPT-5.6 Sol leads

Coding

Like-for-like
GPT-5.6 Sol
67.1
Supported · #11/156
Inkling-Small
36.9
Supported · #77/156
Basis
BenchAlign v5.8 lane · 14 vs 6 public rows
Reading
GPT-5.6 Sol leads

Knowledge

Like-for-like
GPT-5.6 Sol
76.3
Supported · #12/179
Inkling-Small
50.6
Supported · #75/179
Basis
BenchAlign v5.8 lane · 8 vs 6 public rows
Reading
GPT-5.6 Sol leads

Multimodal

Directional only
GPT-5.6 Sol
89.9
#7/58
Inkling-Small
67.3
#41/58
Basis
Provisional lane · 1 vs 2 weighted rows
Reading
Directional only

Instruction following

Directional only
GPT-5.6 Sol
89.1
#34/157
Inkling-Small
93.3
#10/157
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Directional only

Reasoning

Not comparable
GPT-5.6 Sol
76.4
#12/26
Inkling-Small
55.0
Unranked · 4 rankable rows
Basis
Provisional lane · 2 vs 1 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

Math

Not comparable
GPT-5.6 Sol
95.8
Unranked · 3 rankable rows
Inkling-Small
69.8
#5/12
Basis
Provisional lane · 2 vs 4 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) 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

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.

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.

Context window

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

GPT-5.6 Sol

Inkling-Small

1M

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

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, 74.83 versus 49.5, 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.

Questions

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

GPT-5.6 Sol has the higher public score, 74.83 versus 49.5, 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 has the higher public coding point estimate, 67.1 to 36.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

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

GPT-5.6 Sol has the higher public agentic tasks point estimate, 68.8 to 36.1, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

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.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence56 rows

Agentic

  • Terminal-Bench 3.0

    GPT-5.6 Sol34.6%
    Source
    Inkling-Small—

    Not directly comparable

  • Terminal-Bench 2.1

    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

  • MazeBench

    GPT-5.6 Sol13%
    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 Sol42.0 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 2.1

    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

  • CursorBench 3.2

    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

  • CursorBench 4.0

    GPT-5.6 Sol41.7%
    Source
    Inkling-Small—

    Not directly comparable

  • PostTrainBench v1.1

    GPT-5.6 Sol36.2%
    Source
    Inkling-Small—

    Not directly comparable

  • FrontierCode 2.0

    GPT-5.6 Sol27.6%
    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

  • ARC-AGI-1

    GPT-5.6 Sol96.50%
    Source
    Inkling-Small84.00%
    Source

    GPT-5.6 Sol leads this result

  • CritPt

    GPT-5.6 Sol—
    Inkling-Small8.3%
    Source

    Not directly comparable

Multimodal

  • ExtractBench (LlamaIndex)

    GPT-5.6 Sol93.77%
    Source
    Inkling-Small—

    Not directly comparable

  • ParseBench

    GPT-5.6 Sol74.46%
    Source
    Inkling-Small—

    Not directly comparable

  • 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

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

Instruction following

  • Gray Swan IPI (15 attempts)

    GPT-5.6 Sol27.0%
    Source
    Inkling-Small—

    Not directly comparable

  • IFBench

    GPT-5.6 Sol—
    Inkling-Small82.2%
    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-Small46.316%
    Source

    GPT-5.6 Sol leads this result

  • FrontierMath v2 (Tier 4)

    GPT-5.6 Sol83.000%
    Source
    Inkling-Small17.073%
    Source

    GPT-5.6 Sol leads this result

  • 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

56 public results · 16 shared

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Last updated October 29, 2026