RankingEffort benchmarks

DeepSeek V4.1 Flash · High

Compare models

45 measured results · 5 effort settings · 24 benchmark/harness combinations

Model evidence and sources →

Change model

Model

Current configurationSources

Compare with

Choose a second model and its effort to see both profiles and benchmark differences below.

Compare withModel and configuration

Capability profile

One configuration, seven capabilities

Comparison score · 0–100

ADeepSeek V4.1 Flash · High1 of 7 capabilities supported

Gaps are unknown, not zero. Hollow points are preliminary.

Agentic
Unknown
Hard reasoning
A47.0Supported
Coding
A85.4Preliminary
Human pref
Unknown
Knowledge
Unknown
Multimodal
Unknown
Long context
Unknown

Each profile belongs to the named configuration. Capability scores use a shared panel for all axes, distinct from the overall ranking panel; they are not accuracy percentages or direct head-to-head wins.

Capability score evidence

DeepSeek V4.1 Flash · High: 70.2 overall comparison score. Meets the overall evidence requirements.

2 areas measured. The available task mix affects this estimate; missing areas remain unknown.

Which sources carry the weight?

Cognition · 51.9% direct comparison weight · independent of the model provider
ARC Prize · 48.1% direct comparison weight · independent of the model provider

Which benchmark families carry the weight?

FrontierCode · 51.9% direct comparison weight
ARC-AGI · 27.6% direct comparison weight
arc-agi-3 · 20.5% direct comparison weight

These shares describe direct comparison weight, not fractions of the final score or confidence. Source balancing does not give every family equal weight or remove correlations between overlapping sources.

How sensitive is this score?

The audit removes one source at a time and refits against the same overall reference panel. These published results use the matching dataset audited 2026-10-20.

Both ranks use the same surviving configurations for each removal. The cohort starts with 444 configurations supported in the original audit, including separate effort settings. These are diagnostic positions, not the default leaderboard ranks. Eligibility is not rechecked after removal.

What changes when a source is removed?
Removed source	Rank before → after	Rank movement	Cohort remaining / lost support	Score after (change)
Artificial Analysis	41 → 43	Down 2	203 remaining / 241 lost	69.8 (-0.4 points)
ARC Prize	41 → 10	Up 31	444 remaining / 0 lost	90.4 (+20.3 points)
Datacurve	41 → 39	Up 2	444 remaining / 0 lost	65.0 (-5.2 points)
LiveCodeBench	41 → 41	No movement	444 remaining / 0 lost	70.2 (+0.0 points)
Scale	41 → 41	No movement	444 remaining / 0 lost	71.1 (+0.9 points)
Terminal-Bench	41 → 39	Up 2	444 remaining / 0 lost	70.2 (+0.0 points)
Cognition	41 → 76	Down 35	444 remaining / 0 lost	44.2 (-25.9 points)
LiveBench	41 → 41	No movement	443 remaining / 1 lost	71.3 (+1.2 points)
SWE-rebench	41 → 41	No movement	444 remaining / 0 lost	69.6 (-0.5 points)
Epoch AI	41 → 41	No movement	431 remaining / 13 lost	71.4 (+1.2 points)
Vals AI	41 → 42	Down 1	443 remaining / 1 lost	69.9 (-0.3 points)
Provider reports · Anthropic	41 → 41	No movement	444 remaining / 0 lost	70.1 (-0.0 points)
Provider reports · Moonshot AI	41 → 41	No movement	444 remaining / 0 lost	69.8 (-0.3 points)
Provider reports · Meta	41 → 40	Up 1	444 remaining / 0 lost	70.1 (-0.0 points)
Provider reports · Mistral	41 → 41	No movement	444 remaining / 0 lost	70.2 (+0.0 points)
Provider reports · OpenAI	41 → 42	Down 1	444 remaining / 0 lost	70.2 (+0.0 points)
All provider reports	41 → 41	No movement	444 remaining / 0 lost	69.8 (-0.4 points)

Lost support means a configuration no longer has a comparison path to the complete reference panel. Its rank is unavailable. A surviving path alone does not establish leaderboard eligibility.

Overlapping sources may remain correlated even with source balancing. Leave-one-source-out movement is a sensitivity diagnostic, not a spread of source-specific ranks or a confidence measure. Scoring methodology · Dated configuration audit

Every benchmark family

Removed evidence	Recomputed score	Change
frontiercode	44.2	-25.9
deepswe	65.0	-5.2
arc-agi-3	73.7	+3.5
arc-agi	73.0	+2.8
mmmu-pro	70.8	+0.6
hle	70.7	+0.6
swe-rebench	69.6	-0.5
simpleqa	70.6	+0.5
mmlu-pro	70.6	+0.4
gpqa	69.8	-0.4
epoch-game-puzzles	69.8	-0.3
ifbench	69.9	-0.3
multi-swe-bench	69.9	-0.2
swe-atlas-qna	69.9	-0.2
swe-atlas-test-writing	70.0	-0.2
automationbench	70.0	-0.2
tau-bench	70.0	-0.2
harvey	70.0	-0.2
livebench-data	70.3	+0.2
terminal-bench	70.3	+0.2
vals-finance-agent	70.0	-0.1
gdp-pdf	70.3	+0.1
aime	70.0	-0.1
livebench-instructions	70.3	+0.1
livebench-reasoning	70.1	-0.1
vals-tax-agent	70.1	-0.1
enigma-eval	70.1	-0.1
apex-agents	70.2	+0.1
livebench-language	70.2	+0.1
frontiermath	70.1	-0.1
critpt	70.1	-0.1
vibe-code	70.1	-0.1
gdpval	70.2	+0.1
omniscience	70.2	+0.1
itbench	70.1	-0.0
vals-legal-research	70.1	-0.0
livecodebench	70.2	+0.0
swe-atlas-refactoring	70.1	-0.0
vals-excel-modeling	70.1	-0.0
livebench-coding	70.1	-0.0
enterprise-ops	70.1	-0.0
briefcase	70.2	+0.0
livebench-math	70.2	+0.0
vals-code-migration	70.2	+0.0
analyst-agent	70.2	+0.0
aa-lcr	70.2	+0.0
gmmlu	70.2	-0.0
swe-bench-pro	70.2	+0.0
terminal-bench-science	70.2	+0.0
math500	70.2	-0.0

What evidence is missing from the fit?

Across all collected settings for this model: 49 observations, 39 contributing, 0 matched without graph weight and 10 excluded. Counts do not establish rank eligibility.

3 · Benchmark family or source protocol has not been reviewed
2 · Original SciCode grading defects are under review; retained as supporting evidence, excluded from aggregate and capability scores. Corrected SciCode-Verified requires a separate protocol review. Sources: https://arxiv.org/abs/2608.04975 and https://artificialanalysis.ai/evaluations/scicode
1 · Evaluator has not been reviewed for independent admission
3 · Supporting evidence outside the reviewed capability core
1 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately

Inspect every observation and exclusion →

Benchmark results

These are published benchmark scores. Supported effort estimates also appear on the Capability leaderboard. Results from different harnesses occupy different rows. Missing cells stay unknown; no scores are copied between effort levels.

Benchmark / source	Low	High	Max	None	Non-reasoning
AA-AnalystAgentArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of tasks solved on all 5 of 5 attempts · 80 tasks, 5 attempts per task · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	35% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	Not reported
AA-Briefcase EloArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Briefcase v1.1 is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-10-18.	Not reported	Not reported	1,420.2 Elo Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	1,117.62 Elo Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
AA-LCR v1.1Artificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	84% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	55.33% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
AutomationBench-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of task objectives completed with no guardrail violations · Higher is better · Benchmark developed by Zapier · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	68.89% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	47.81% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
CritPtArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark developed by Argonne and UIUC, with contributions from 60+ researchers globally. CritPt is under review by its authors following external feedback · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	14.29% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	0.29% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
GDP.pdf: All-pass RateArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of attempts where every atomic criterion passed · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	12.8% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	3.8% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
GDPval-AA v2.1 LeaderboardArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Elo rating for performance on real-world work tasks · Anchored to DeepSeek V4.1 Flash (max) at 1600 · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-10-18.	Not reported	Not reported	1,600 Elo Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	1,341.23 Elo Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
Harvey LAB-AA v1.1: Hallucination-Gated All-Pass RateArtificial Analysis · Stirrup; Harvey private dataset v1.1.0; 120 tasks across 24 practice areas; up to 200 turns; internet disabled; GPT-6 Sol, Grok 4.7 and Claude Opus 5.5 rubric judges; GPT-6 Sol High two-pass hallucination check; hallucination-gated all-pass averaged across judges Benchmark details Average over tasks of the share of the judge panel finding every rubric criterion passed, with a task zeroed on any material hallucination · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	1.67% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	Not reported
Humanity's Last ExamArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	39.25% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	10.8% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
ITBench-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Combined public and private Site Reliability Engineering (SRE) tasks · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	46.92% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	Not reported
MLCR-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of tasks judged accurate, complete, and concise · Expert + compound (hard) sets · Benchmark developed by Wisedocs · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	22.78% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	Not reported
MMMU-ProArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	76.99% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	65.61% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
AA-Omniscience IndexArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis Unit: index. Source collected 2026-10-18.	Not reported	Not reported	-5.3 Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	-10.18 Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
AA-Omniscience AccuracyArtificial Analysis · 6000 questions; 1 attempt; correct-answer share; GPT-5.6 Luna medium grader Benchmark details AA-Omniscience Accuracy (higher is better) measures the proportion of correctly answered questions out of all questions, regardless of whether the model chooses to answer · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	46.4% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	28.45% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
SciCodeArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark curated by scientists across 16 disciplines. SciCode is under review following an independent audit of the dataset · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	51.85% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	35.53% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
Terminal-Bench-Science 0.1Artificial Analysis · mini-swe-agent; Terminal-Bench-Science 0.1.0; 70 tasks; pass@1 averaged over 3 repeats Benchmark details Share of tasks passed (pass@1), averaged over three repeats · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	9.05% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	Not reported
Terminal-Bench v4.0Artificial Analysis · mini-SWE-agent v2.4.6; 66 tasks; pass@1 averaged over 3 repeats; 500 steps; task timeout up to 8 hours Benchmark details Benchmark developed by the Laude Institute, Stanford, and open-source contributors · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	26.77% Reported settings DeepSeek V4.1 Flash (Max); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash	Not reported	5.56% Reported settings DeepSeek V4.1 Flash (Non-reasoning); Model source: https://artificialanalysis.ai/models/deepseek-v4-1-flash-non-reasoning
ARC-AGI-2ARC Prize · v2 Semi-Private Benchmark details Original public board. Configuration and task coverage may differ; inspect source. Unit: percent. Source collected 2026-10-18.	60.56% Reported settings DeepSeek V4.1 Flash (Low); Source model ID: deepseek-v4-1-flash-low; 120 tasks	67.5% Reported settings DeepSeek V4.1 Flash (High); Source model ID: deepseek-v4-1-flash-high; 120 tasks	72.92% Reported settings DeepSeek V4.1 Flash (Max); Source model ID: deepseek-v4-1-flash-max; 120 tasks	1.25% Reported settings DeepSeek V4.1 Flash (None); Source model ID: deepseek-v4-1-flash-none; 120 tasks	Not reported
ARC-AGI-3 · provider-adapterARC Prize · Provider Adapter Benchmark details ARC-AGI-3; Provider Adapter. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-18.	3.26% Reported settings ARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group deepseek-v4-1-flash; variant provider-adapter-low; public-demo task scores are excluded	3.15% Reported settings ARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group deepseek-v4-1-flash; variant provider-adapter-high; public-demo task scores are excluded	2.68% Reported settings ARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group deepseek-v4-1-flash; variant provider-adapter-max; public-demo task scores are excluded	0.48% Reported settings ARC-AGI-3 Semi-Private verified summary; Provider Adapter harness; source group deepseek-v4-1-flash; variant provider-adapter-none; public-demo task scores are excluded	Not reported
ARC-AGI-3 · standardARC Prize · Standard Benchmark details ARC-AGI-3; Standard. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-18.	0.35% Reported settings ARC-AGI-3 Semi-Private verified summary; Standard harness; source group deepseek-v4-1-flash; variant low; public-demo task scores are excluded	0.48% Reported settings ARC-AGI-3 Semi-Private verified summary; Standard harness; source group deepseek-v4-1-flash; variant high; public-demo task scores are excluded	0.85% Reported settings ARC-AGI-3 Semi-Private verified summary; Standard harness; source group deepseek-v4-1-flash; variant max; public-demo task scores are excluded	0.34% Reported settings ARC-AGI-3 Semi-Private verified summary; Standard harness; source group deepseek-v4-1-flash; variant none; public-demo task scores are excluded	Not reported
FrontierCode 1.1 · extended-chiselCognition · chisel Benchmark details FrontierCode 1.1; chisel. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-18.	Not reported	56.62% Reported settings FrontierCode 1.1; extended; 150 tasks; chisel; source effort high; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.0049	Not reported	Not reported	Not reported
FrontierCode 1.1 · main-chiselCognition · chisel Benchmark details FrontierCode 1.1; chisel. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-18.	Not reported	43.87% Reported settings FrontierCode 1.1; main; 100 tasks; chisel; source effort high; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.0073	Not reported	Not reported	Not reported
Artificial Analysis Cyber IndexArtificial Analysis · Artificial Analysis Stirrup; defensive code audit, patch and end-to-end vulnerability tasks Benchmark details v1.0. Equal mean of CWE-Bench-AA, DeepsecBench-AA and CyberGym-E2E-AA. Display only. This composite measures defensive source-code tasks. Successful capability scores depend on safety refusals, and refusal rates are reported separately. It does not enter weighted Overall. https://artificialanalysis.ai/methodology/cyber-index Unit: index. Source collected 2026-10-18.	Not reported	Not reported	40.81 Reported settings Artificial Analysis Stirrup; v1.0; DeepSeek V4.1 Flash (Max); source label DeepSeek V4.1 Flash (Max); mitigation standard; public model; source field cyberIndex; index 0–100; CWE-Bench-AA pass@1 0.683333333333333; refusal 0; DeepsecBench-AA median F2, 3 repeats, GPT-5.6 Sol High judge 0.31199859972578; refusal 0; CyberGym-E2E-AA pass@1 0.22900763358778625; refusal 0; https://artificialanalysis.ai/models/deepseek-v4-1-flash; page sha256 344ca66f5aa3f3abd1901b12bd29db73950d90e553fcb3ae900dcf590d7a6db2; encrypted payload sha256 b5e6ae259181eaed471e288c4bbdbd1088438e0a81caf19ec0fa60f7092d48f7; Display only. This composite measures defensive source-code tasks. Successful capability scores depend on safety refusals, and refusal rates are reported separately. It does not enter weighted Overall.	Not reported	Not reported
LMArena Agent ArenaLMArena · Arena Agent Mode. The board does not name a per-model scaffold. Benchmark details Aggregate Agent Arena IPS net improvement, stored as the board's printed percentage points. Arena Agent Mode does not name a per-model scaffold. Display only. Excluded from weighted Overall. Unit: index. Source collected 2026-10-18.	Not reported	Not reported	4.02 Reported settings Deepseek V4.1 Flash (Max); Arena Agent Mode; IPS net improvement 4.02 points ±0.47. rank 17; observations 16932092; sessions 112938; published 2026-10-02. The board does not name a per-model scaffold. Display only. Excluded from weighted Overall.	Not reported	Not reported

What these comparisons mean

Each source reports its own effort labels. Matching labels do not establish equal compute budgets or identical fallback behavior. Open Reported settings to inspect the exact model name, agent and task coverage. Multiple results at one level remain visible rather than selecting the best. Source-reported None or Non-reasoning labels are not treated as evidence that an API supports those settings.

These measurements use their own dated source collection. The leaderboard fits identified configurations jointly; it contains no pooled model ratings. Explicit thinking budgets are separate configurations. Read the methodology.

Download all effort benchmark results · 8,915 results across 259 models · Collected 2026-10-18

DeepSeek V4.1 Flash · High

Compare with

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context

Capability score evidence

Benchmark results