Gemini 4 Argon vs Inkling 2 Small

Updated November 7, 2026. Rank says Gemini 4 Argon is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Gemini 4 Argon has the higher public point estimate, 82.1 versus 59.06. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Gemini 4 Argon

Google

82.1/100

Supported · Public rank #5

90% interval 78.8–85.4

Model B

Inkling 2 Small

Thinking Machines Lab

59.06/100

Estimated · Public rank #56

Conditional range 44.7–73.4

Shared results: 2
Gemini 4 Argon only: 30
Inkling 2 Small only: 23
Like-for-like categories: 2 / 8

Supported: Gemini 4 Argon · Estimated: Inkling 2 Small. Conditional ranges do not establish rank confidence.How 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
Gemini 4 Argon
Gemini 4 Argon has the higher public coding point estimate, 72.2 to 59.7, 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
Gemini 4 Argon
Gemini 4 Argon has the higher public agentic point estimate, 77.7 to 59.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Inkling 2 Small
Inkling 2 Small 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

Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Inkling 2 Small
Inkling 2 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 2 Small
Inkling 2 Small has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented

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.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

72.2Gemini 4 Argon59.7Inkling 2 Small

Like-for-like · BenchAlign v5.8

Gemini 4 Argon 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.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

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

Gemini 4 Argon: 77.7; Supported · #3/131
Inkling 2 Small: 59.9; Supported · #26/131
Basis: BenchAlign v5.8 lane · 10 vs 5 public rows
Reading: Gemini 4 Argon leads · intervals overlap

Coding

Like-for-like

Gemini 4 Argon: 72.2; Supported · #6/157
Inkling 2 Small: 59.7; Supported · #20/157
Basis: BenchAlign v5.8 lane · 7 vs 6 public rows
Reading: Gemini 4 Argon leads · intervals overlap

Knowledge

Directional only

Gemini 4 Argon: 80.5; Supported · #8/178
Inkling 2 Small: 60.4; Estimated · #46/178
Basis: BenchAlign v5.8 lane · 1 vs 2 public rows
Reading: Directional only

Reasoning

Not comparable

Gemini 4 Argon: 85.2; #3/25
Inkling 2 Small: 86.1; Unranked · 2 rankable rows
Basis: Provisional lane · 2 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Gemini 4 Argon: Not ranked
Inkling 2 Small: 86.6; #12/59
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Gemini 4 Argon: Not ranked
Inkling 2 Small: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Gemini 4 Argon: Not ranked
Inkling 2 Small: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Gemini 4 Argon: 89.3; Unranked · 2 rankable rows
Inkling 2 Small: 85.9; Unranked · 2 rankable rows
Basis: Provisional lane · 2 vs 1 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Gemini 4 Argon and Inkling 2 Small
Category	Gemini 4 Argon	Inkling 2 Small	Basis	Reading
Agentic	77.7Supported · #3/131	59.9Supported · #26/131	Like-for-likeBenchAlign v5.8 lane · 10 vs 5 public rows	Gemini 4 Argon leads · intervals overlap
Coding	72.2Supported · #6/157	59.7Supported · #20/157	Like-for-likeBenchAlign v5.8 lane · 7 vs 6 public rows	Gemini 4 Argon leads · intervals overlap
Knowledge	80.5Supported · #8/178	60.4Estimated · #46/178	Directional onlyBenchAlign v5.8 lane · 1 vs 2 public rows	Directional only
Reasoning	85.2#3/25	86.1Unranked · 2 rankable rows	Not comparableProvisional lane · 2 vs 1 weighted rows	Not comparable
Multimodal	Not ranked	86.6#12/59	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	89.3Unranked · 2 rankable rows	85.9Unranked · 2 rankable rows	Not comparableProvisional lane · 2 vs 1 weighted rows	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

Gemini 4 Argon: $0.007; Fits in one request
Inkling 2 Small: $0.0008; Fits in one request

Inkling 2 Small has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 4 Argon: $0.13; Fits in one request
Inkling 2 Small: $0.018; Fits in one request

Inkling 2 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

Gemini 4 Argon: $0.16; Fits in one request
Inkling 2 Small: $0.022; Fits in one request

Inkling 2 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.

SpecificationGemini 4 ArgonInkling 2 Small

Context window

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

Gemini 4 Argon

Google Gemini 4 Argon model documentation

Inkling 2 Small

Tinker models and pricing

API model ID

Gemini 4 Argon

gemini-4-argon

Google Gemini 4 Argon model documentation

Inkling 2 Small

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Gemini 4 Argon

$0.1 per 1M cached input tokens

Google Gemini API pricing

Inkling 2 Small

$0.03 per 1M cached input tokens

Tinker models and pricing

Documented inputs

Gemini 4 Argon

text, image, video, audio, pdf

Google Gemini 4 Argon model documentation

Inkling 2 Small

Not sourced

Documented outputs

Gemini 4 Argon

text

Google Gemini 4 Argon model documentation

Inkling 2 Small

Not sourced

Provider availability

Gemini 4 Argon

Generally Available · Gemini API, Google AI Studio

Google Gemini 4 Argon model documentation

Inkling 2 Small

Not sourced

Reasoning profile

Gemini 4 Argon

Reasoning

Inkling 2 Small

Hybrid

Weight access

Gemini 4 Argon

Proprietary

Inkling 2 Small

Proprietary

License

Gemini 4 Argon

Proprietary

Inkling 2 Small

Proprietary

Release date

Gemini 4 Argon

2026-09-30

Inkling 2 Small

2026-11-05

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: Gemini 4 Argon has the higher public point estimate, 82.1 versus 59.06. Their conditional score ranges do not overlap. These ranges do not establish rank confidence.
Workload cost: Repository review: $0.13 vs $0.018. Cache-heavy agent loop: $0.16 vs $0.022.
Context tradeoff: Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 4 Argon or Inkling 2 Small?

Gemini 4 Argon has the higher public point estimate, 82.1 versus 59.06. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 4 Argon or Inkling 2 Small?

Gemini 4 Argon has the higher public coding point estimate, 72.2 to 59.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Gemini 4 Argon or Inkling 2 Small?

Gemini 4 Argon has the higher public agentic tasks point estimate, 77.7 to 59.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, Gemini 4 Argon or Inkling 2 Small?

For the stated presets, chat costs $0.007 on Gemini 4 Argon and $0.0008 on Inkling 2 Small; repository review costs $0.13 and $0.018; the cache-heavy agent loop costs $0.16 and $0.022. Costs use the listed standard API rates.

Which has the larger context window, Gemini 4 Argon or Inkling 2 Small?

Both models list the same context window, 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 evidence55 rows

Agentic

AutomationBench
Gemini 4 Argon51.3%
Source
Inkling 2 Small—
Not directly comparable
Finance Agent v2
Gemini 4 Argon65.4%
Source
Inkling 2 Small—
Not directly comparable
Terminal-Bench 4.0
Gemini 4 Argon57.40%
Source
Inkling 2 Small—
Not directly comparable
Agents' Last Exam
Gemini 4 Argon39.5%
Source
Inkling 2 Small—
Not directly comparable
OSWorld 2.0
Gemini 4 Argon69.2%
Source
Inkling 2 Small—
Not directly comparable
CWE-bench v1
Gemini 4 Argon68.0%
Source
Inkling 2 Small—
Not directly comparable
Terminal-Bench-Science 0.1 (6x verifier timeout)
Gemini 4 Argon57.6%
Source
Inkling 2 Small—
Not directly comparable
MazeBench
Gemini 4 Argon12%
Source
Inkling 2 Small—
Not directly comparable
OSWorld 2.1 Offline
Gemini 4 Argon74.7%
Source
Inkling 2 Small—
Not directly comparable
ExploitGym
Gemini 4 Argon39.5%
Source
Inkling 2 Small—
Not directly comparable
Terminal-Bench 2.1
Gemini 4 Argon—
Inkling 2 Small85.1%
Source
Not directly comparable
BrowseComp
Gemini 4 Argon—
Inkling 2 Small90.2%
Source
Not directly comparable
DeepSearchQA
Gemini 4 Argon—
Inkling 2 Small90.9%
Source
Not directly comparable
MCP Atlas
Gemini 4 Argon—
Inkling 2 Small85%
Source
Not directly comparable
JobBench
Gemini 4 Argon—
Inkling 2 Small70.5%
Source
Not directly comparable

Coding

ScarfBench
Gemini 4 Argon75.2%
Source
Inkling 2 Small—
Not directly comparable
DeepSWE
Gemini 4 Argon77.9%
Source
Inkling 2 Small72.1%
Source
Gemini 4 Argon leads this result
FrontierSWE v2
Gemini 4 Argon55.0%
Source
Inkling 2 Small—
Not directly comparable
Vibe Code Bench
Gemini 4 Argon91.90%
Source
Inkling 2 Small—
Not directly comparable
PostTrainBench v1.1
Gemini 4 Argon45.3%
Source
Inkling 2 Small—
Not directly comparable
Bug Hunt Bench
Gemini 4 Argon40.7 fixes
Source
Inkling 2 Small—
Not directly comparable
FrontierCode 2.0
Gemini 4 Argon26.3%
Source
Inkling 2 Small—
Not directly comparable
SWE-bench Verified
Gemini 4 Argon—
Inkling 2 Small82.2%
Source
Not directly comparable
SWE Multilingual
Gemini 4 Argon—
Inkling 2 Small81.2%
Source
Not directly comparable
sweMarathon
Gemini 4 Argon—
Inkling 2 Small38.8%
Source
Not directly comparable
Terminal-Bench 2.1
Gemini 4 Argon—
Inkling 2 Small85.1%
Source
Not directly comparable
PostTrainBench v1.2
Gemini 4 Argon—
Inkling 2 Small31.9%
Source
Not directly comparable

Reasoning

STEMBench
Gemini 4 Argon2.44
Source
Inkling 2 Small—
Not directly comparable
Graphwalks BFS 128K
Gemini 4 Argon99.7%
Source
Inkling 2 Small—
Not directly comparable
GraphWalks BFS 256K–1M
Gemini 4 Argon84.2%
Source
Inkling 2 Small—
Not directly comparable
ARC-AGI-1
Gemini 4 Argon98.50%
Source
Inkling 2 Small—
Not directly comparable
ARC-AGI-2
Gemini 4 Argon91.3%
Source
Inkling 2 Small—
Not directly comparable
ARC-AGI-3
Gemini 4 Argon46.3%
Source
Inkling 2 Small—
Not directly comparable
ARC-AGI-3 Provider Adapter
Gemini 4 Argon97.30%
Source
Inkling 2 Small—
Not directly comparable
LongBench v2
Gemini 4 Argon—
Inkling 2 Small70.6%
Source
Not directly comparable

Multimodal

ExtractBench Pro
Gemini 4 Argon30%
Source
Inkling 2 Small—
Not directly comparable
Chartography (no tools)
Gemini 4 Argon71.6%
Source
Inkling 2 Small36.7%
Source
Gemini 4 Argon leads this result
LVBench
Gemini 4 Argon91.7%
Source
Inkling 2 Small—
Not directly comparable
Blueprint-Bench 2
Gemini 4 Argon54.4%
Source
Inkling 2 Small—
Not directly comparable
CharXiv
Gemini 4 Argon—
Inkling 2 Small87.7%
Source
Not directly comparable
CharXiv w/o tools
Gemini 4 Argon—
Inkling 2 Small85.6%
Source
Not directly comparable
Chartography (tools)
Gemini 4 Argon—
Inkling 2 Small80.4%
Source
Not directly comparable
BabyVision
Gemini 4 Argon—
Inkling 2 Small68.6%
Source
Not directly comparable
BabyVision w/ Python
Gemini 4 Argon—
Inkling 2 Small93.7%
Source
Not directly comparable
ScreenSpot Pro
Gemini 4 Argon—
Inkling 2 Small83.8%
Source
Not directly comparable
PerceptionBench
Gemini 4 Argon—
Inkling 2 Small64.7%
Source
Not directly comparable
MathVision
Gemini 4 Argon—
Inkling 2 Small92.8%
Source
Not directly comparable

Knowledge

LABBench2
Gemini 4 Argon88.8%
Source
Inkling 2 Small—
Not directly comparable
GPQA
Gemini 4 Argon—
Inkling 2 Small93%
Source
Not directly comparable
GPQA-D
Gemini 4 Argon—
Inkling 2 Small93.0%
Source
Not directly comparable

Instruction following

Gray Swan IPI (15 attempts)
Gemini 4 Argon0.7%
Source
Inkling 2 Small—
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Gemini 4 Argon85.965%
Source
Inkling 2 Small—
Not directly comparable
FrontierMath v2 (Tier 4)
Gemini 4 Argon78.049%
Source
Inkling 2 Small—
Not directly comparable
HMMT Feb 2026
Gemini 4 Argon—
Inkling 2 Small95.8%
Source
Not directly comparable
Apex
Gemini 4 Argon—
Inkling 2 Small63.5%
Source
Not directly comparable

55 public results · 2 shared

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Last updated November 7, 2026

Gemini 4 Argon vs Inkling 2 Small

Decision reading

Which one for your work

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Long documents

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Knowledge

Reasoning

Multimodal

Multilingual

Instruction following

Math

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

If you already use one of these models

Questions

Which is better, Gemini 4 Argon or Inkling 2 Small?

Which is better for coding, Gemini 4 Argon or Inkling 2 Small?

Which is better for agentic tasks, Gemini 4 Argon or Inkling 2 Small?

Which costs less, Gemini 4 Argon or Inkling 2 Small?

Which has the larger context window, Gemini 4 Argon or Inkling 2 Small?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Instruction following

Math

Related comparisons

Watch Gemini 4 Argon vs Inkling 2 Small