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Model A
DeepSeek V4.1 Flash

DeepSeek

Evidence status unavailable

90% interval unavailable

DeepSeek V4.1 Flash vs Inkling

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

Thinking Machines Lab logo
Model B
Inkling

Thinking Machines Lab

60.29/100

Supported · Public rank #66

90% interval 50.470.2

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

3 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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    DeepSeek V4.1 Flash

    DeepSeek V4.1 Flash 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

    DeepSeek V4.1 Flash

    DeepSeek V4.1 Flash 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

    DeepSeek V4.1 Flash

    DeepSeek V4.1 Flash 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

    DeepSeek V4.1 Flash is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    DeepSeek V4.1 Flash is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
3
DeepSeek V4.1 Flash only
18
Inkling only
18
Like-for-like categories
0 / 8

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

Not comparable
DeepSeek V4.1 Flash
Not ranked
Inkling
38.3
Supported · #122/152
Basis
BenchAlign lane · 8 vs 4 public rows
Reading
Not comparable

Coding

Not comparable
DeepSeek V4.1 Flash
Not ranked
Inkling
41.2
Supported · #111/151
Basis
BenchAlign lane · 6 vs 6 public rows
Reading
Not comparable

Reasoning

Not comparable
DeepSeek V4.1 Flash
Not ranked
Inkling
74.1
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
DeepSeek V4.1 Flash
Not ranked
Inkling
57.5
Supported · #43/182
Basis
BenchAlign lane · 3 vs 6 public rows
Reading
Not comparable

Math

Not comparable
DeepSeek V4.1 Flash
Not ranked
Inkling
78.9
Unranked · 1 rankable row
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multilingual

Not comparable
DeepSeek V4.1 Flash
Not ranked
Inkling
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
DeepSeek V4.1 Flash
Not ranked
Inkling
49.2
#38/48
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Instruction following

Not comparable
DeepSeek V4.1 Flash
Not ranked
Inkling
85.2
#43/121
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
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.

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

DeepSeek V4.1 Flash
$0.0009
Fits in one request
Inkling
$0.00421
Fits in one request

DeepSeek V4.1 Flash has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

DeepSeek V4.1 Flash
$0.0186
Fits in one request
Inkling
$0.10754
Fits in one request

DeepSeek V4.1 Flash has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

DeepSeek V4.1 Flash
$0.0192
Fits in one request
Inkling
$0.159
Fits in one request

DeepSeek V4.1 Flash 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.

Cached-input rate

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

DeepSeek V4.1 Flash

$0.006 per 1M cached input tokens

DeepSeek: Models & Pricing

Inkling

$0.374 per 1M cached input tokens

Reasoning profile

DeepSeek V4.1 Flash

Reasoning

Inkling

Hybrid

Weight access

DeepSeek V4.1 Flash

Open Weight

Inkling

Open Weight

License

DeepSeek V4.1 Flash

Open Weight

Inkling

Open Weight

Release date

DeepSeek V4.1 Flash

2026-09-10

Inkling

2026-07-15

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: $0.0186 vs $0.10754. Cache-heavy agent loop: $0.0192 vs $0.159.
Context tradeoff
Both models list 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 evidence39 rows

Agentic

  • Terminal-Bench 2.1

    DeepSeek V4.1 Flash90.6%
    Source
    Inkling

    Not directly comparable

  • terminalBench3

    DeepSeek V4.1 Flash30%
    Source
    Inkling

    Not directly comparable

  • Terminal-Bench 4.0

    DeepSeek V4.1 Flash31.20%
    Source
    Inkling

    Not directly comparable

  • CyberGym

    DeepSeek V4.1 Flash88.1%
    Source
    Inkling

    Not directly comparable

  • ExploitGym

    DeepSeek V4.1 Flash15.3%
    Source
    Inkling

    Not directly comparable

  • HLE w/ tools

    DeepSeek V4.1 Flash63.9%
    Source
    Inkling

    Not directly comparable

  • AutomationBench

    DeepSeek V4.1 Flash54.8%
    Source
    Inkling

    Not directly comparable

  • Agents' Last Exam

    DeepSeek V4.1 Flash31.8%
    Source
    Inkling

    Not directly comparable

  • Terminal-Bench 2.0

    DeepSeek V4.1 Flash
    Inkling63.8%
    Source

    Not directly comparable

  • BrowseComp

    DeepSeek V4.1 Flash
    Inkling77.1%
    Source

    Not directly comparable

  • MCP Atlas

    DeepSeek V4.1 Flash
    Inkling74.1%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    DeepSeek V4.1 Flash
    Inkling47.6%
    Source

    Not directly comparable

Coding

  • Codeforces

    DeepSeek V4.1 Flash3471.0
    Source
    Inkling

    Not directly comparable

  • Terminal-Bench 2.1

    DeepSeek V4.1 Flash90.6%
    Source
    Inkling

    Not directly comparable

  • terminalBench3

    DeepSeek V4.1 Flash30%
    Source
    Inkling

    Not directly comparable

  • DeepSWE

    DeepSeek V4.1 Flash74.2%
    Source
    Inkling

    Not directly comparable

  • ProgramBench

    DeepSeek V4.1 Flash20.3%
    Source
    Inkling

    Not directly comparable

  • NL2Repo

    DeepSeek V4.1 Flash65.4%
    Source
    Inkling

    Not directly comparable

  • SWE-bench Verified

    DeepSeek V4.1 Flash
    Inkling77.6%
    Source

    Not directly comparable

  • SWE-bench Pro

    DeepSeek V4.1 Flash
    Inkling54.3%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    DeepSeek V4.1 Flash
    Inkling63.8%
    Source

    Not directly comparable

  • FrontierSWE v2

    DeepSeek V4.1 Flash
    Inkling4.1%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    DeepSeek V4.1 Flash
    Inkling85.5%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    DeepSeek V4.1 Flash
    Inkling77.6%
    Source

    Not directly comparable

Knowledge

  • GPQA

    DeepSeek V4.1 Flash90.9%
    Source
    Inkling87.9%
    Source

    DeepSeek V4.1 Flash leads this result

  • GPQA-D

    DeepSeek V4.1 Flash90.9%
    Source
    Inkling87.9%
    Source

    DeepSeek V4.1 Flash leads this result

  • HLE

    DeepSeek V4.1 Flash36.8%
    Source
    Inkling46%
    Source

    Inkling leads this result

  • HLE w/o tools

    DeepSeek V4.1 Flash
    Inkling30%
    Source

    Not directly comparable

  • GPQA Diamond (Vals)

    DeepSeek V4.1 Flash
    Inkling87.1%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    DeepSeek V4.1 Flash
    Inkling86.3%
    Source

    Not directly comparable

Math

  • Apex

    DeepSeek V4.1 Flash65.6%
    Source
    Inkling

    Not directly comparable

  • AIME26

    DeepSeek V4.1 Flash
    Inkling97.1%
    Source

    Not directly comparable

Multimodal

  • Chartography (tools)

    DeepSeek V4.1 Flash78.9%
    Source
    Inkling

    Not directly comparable

  • BabyVision w/ Python

    DeepSeek V4.1 Flash89.6%
    Source
    Inkling

    Not directly comparable

  • ZeroBench w/ Python

    DeepSeek V4.1 Flash49.0%
    Source
    Inkling

    Not directly comparable

  • MMMU-Pro

    DeepSeek V4.1 Flash
    Inkling73.5%
    Source

    Not directly comparable

  • CharXiv

    DeepSeek V4.1 Flash
    Inkling82%
    Source

    Not directly comparable

  • CharXiv w/o tools

    DeepSeek V4.1 Flash
    Inkling78.1%
    Source

    Not directly comparable

Instruction following

  • IFBench

    DeepSeek V4.1 Flash
    Inkling79.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, DeepSeek V4.1 Flash or Inkling?

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, DeepSeek V4.1 Flash or Inkling?

DeepSeek V4.1 Flash is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, DeepSeek V4.1 Flash or Inkling?

DeepSeek V4.1 Flash is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, DeepSeek V4.1 Flash or Inkling?

For the stated presets, chat costs $0.0009 on DeepSeek V4.1 Flash and $0.00421 on Inkling; repository review costs $0.0186 and $0.10754; the cache-heavy agent loop costs $0.0192 and $0.159. Costs use the listed standard API rates.

Which has the larger context window, DeepSeek V4.1 Flash or Inkling?

Both models list the same context window, 1M.

Related comparisons

Last updated September 10, 2026

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