DeepSeek

DeepSeek V4.1 Flash

deepseek/deepseek-v4.1-flash

Model weightsReleased Sep 10, 2026MIT

ThinkingToolsVisionopen weights

DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on...

Run in ChatOSS Cloud Plans

Cost / 1M tokens

Very low usage

$0.14

input

$0.0042

cached input

$0.42

output

Context Window

Up to 131K max output

Architecture

552B total · 32B active MoE

text + image → text

Quickstart & API

deepseek/deepseek-v4.1-flash

Open the model picker in ChatOSS Desktop (Code, Kanban, or Chat) and select or paste this model ID.

Best for & Strengths

Key Strengths

Agentic coding1M context windowUltra-low cache cost ($0.003/M)Fast throughputMIT open weights

Recommended Workloads in ChatOSS

Autonomous coding agents
Full-stack web app generation
High-volume agent loops

Available in ChatOSS Code, Kanban Orchestrate, and Chat modes via Plus, Max, or BYOK.

Verified Evaluations

Benchmarks & Frontier Comparison

How DeepSeek V4.1 Flash compares against leading open-weight and proprietary frontier models across independent agentic coding and reasoning suites.

View full Top 40 Leaderboard →

DeepSeek V4.1 FlashDeepSeek V4.1 FlashGLM 5.3Kimi K3.1 Pro

Benchmark (Metric)	DeepSeek V4.1 Flash	DeepSeek V4.1 Flash	GLM 5.3	Kimi K3.1 Pro	Claude Opus 5.5
Agentic & Software Engineering
ChatOSS Agentic Coding Index (%)	63.2%	63.2%	58.3%	65%	74.1%
SWE-Bench Verified (%)	—	91.5%	95.4%	94.8%	97%
DeepSWE v1.1 (Pass@1 %)	77%	77%	69%	73.5%	74.2%
Vibe Code Bench v1.1 (%)	87.73%	87.7%	78.1%	88.4%	90.3%
Terminal-Bench 4.0 (%)	42.3%	42.3%	42%	46.2%	65.2%
Code Migration (%)	45.62%	45.6%	44.2%	52%	66.7%
Intelligence & Token Economics
Artificial Analysis Intelligence Index (0–100)	24.7	39.5	44.8	55.1	57.6
Input Price (/ 1M tokens)	$0.14	$0.15	$1.40	$2.00	$4.00
Output Price (/ 1M tokens)	$0.42	$0.60	$4.40	$10.00	$20.00

ChatOSS Agentic Coding Index

ChatOSS Benchmark Audit · 4-benchmark composite mean

63.2%

DeepSWE v1.1

DeepSWE / Official Audit · Mini-SWE-Agent

77%

Vibe Code Bench v1.1

Vals.ai · OpenHands

87.73%

Terminal-Bench 4.0

Vals.ai / Artificial Analysis · Terminus 2

42.3%

Terminal-Bench 2.1

Vals.ai · Terminus 2

90.6%

Code Migration

Vals.ai · Vals evaluation harness

45.62%

AutomationBench

Artificial Analysis v4.3

67%

CyberGym (Pass@1)

Model Release Evaluation

88.1%

Artificial Analysis Intelligence Index

Artificial Analysis

24.7

GPQA Diamond (Pass@1)

Benchmark Audit

90.9%

Humanity's Last Exam (Pass@1)

Artificial Analysis / Audit

43%

Active Provider Endpoints (41)

Upstream inference providers serving DeepSeek V4.1 Flash, with per-provider pricing, context limits, quantization, and 24-hour uptime.

Provider	Input / 1M	Output / 1M	Cache Read / 1M	Context	Max Output	Quantization	Uptime (24h)
OpenInferencecache open-inference/fp4	$0.012	$1.80	$0.0058	1M	944K	fp4	100.0%
Relacecache relace	$0.07	$0.50	$0.008	1M	944K	—	100.0%
Decartcache decart/fp4	$0.09	$0.18	$0.018	1M	262K	fp4	97.9%
Sail Researchcache sail-research/fp4/us	$0.09	$0.25	$0.006	1M	384K	fp4	100.0%
Sail Researchcache sail-research/fp4	$0.09	$0.25	$0.006	1M	384K	fp4	100.0%
InferenceNetcache inference-net/us	$0.103	$0.60	$0.008	1M	393K	fp8	100.0%
InferenceNetcache inference-net/fp8	$0.103	$0.60	$0.008	1M	393K	fp8	100.0%
Rekacache reka	$0.105	$0.84	$0.007	1M	393K	—	99.3%
DeepInfracache deepinfra/fp8/flex	$0.112	$0.336	$0.0034	1M	131K	fp8	99.1%
Morphcache morph/fp8	$0.123	$0.368	$0.004	1M	944K	fp8	100.0%
CoreWeavecache coreweave/fp8	$0.13	$0.65	$0.002	1M	944K	fp8	99.1%
AtlasCloudcache atlas-cloud/fp8	$0.135	$0.54	$0.013	1M	393K	fp8	100.0%
Baiducache baidu/fp8	$0.14	$0.559	$0.0028	1M	393K	fp8	100.0%
DeepInfracache deepinfra/fp8	$0.14	$0.42	$0.0042	1M	131K	fp8	100.0%
StreamLakecache streamlake/fp8	$0.147	$0.588	$0.0029	1M	384K	fp8	100.0%
Alibabacache alibaba	$0.165	$0.66	$0.017	1M	393K	—	100.0%
ModelRuncache modelrun/fp4	$0.17	$0.67	$0.006	1M	131K	fp4	100.0%
GMICloudcache gmicloud/fp8	$0.18	$0.72	$0.0036	1M	944K	fp8	99.4%
Wafercache wafer/mxfp4	$0.19	$0.65	$0.012	1M	944K	mxfp4	100.0%
Novitacache novita/fp8	$0.195	$0.78	$0.0039	1M	393K	fp8	100.0%
Mancer 2 mancer/fp8	$0.20	$1.00	—	1M	944K	fp8	92.8%
DeepInfracache deepinfra/fp8/priority	$0.21	$0.63	$0.0063	1M	131K	fp8	92.5%
Fireworkscache fireworks/spot	$0.21	$0.84	$0.0042	1M	944K	—	100.0%
Phalacache phala	$0.21	$0.84	$0.0042	1M	944K	—	100.0%
DigitalOceancache digitalocean	$0.225	$0.90	$0.006	1M	944K	—	100.0%
Makoracache makora/fp8	$0.26	$1.17	$0.0058	1M	944K	fp8	99.9%
Crusoecache crusoe/fp8	$0.29	$1.20	$0.007	1M	944K	fp8	100.0%
Googlecache google-vertex/global	$0.30	$1.20	$0.03	1M	944K	—	100.0%
Nebiuscache nebius/fp8	$0.30	$1.20	$0.01	1M	943K	fp8	99.0%
PrimeIntellectcache primeintellect	$0.30	$1.20	$0.006	1M	131K	—	100.0%
Coherecache cohere	$0.30	$1.20	$0.003	1M	384K	—	99.1%
BaseTencache baseten/us	$0.30	$1.20	$0.007	1M	262K	—	100.0%
Togethercache together	$0.30	$1.20	$0.006	1M	944K	—	100.0%
SiliconFlowcache siliconflow/fp8	$0.30	$1.20	$0.006	1M	393K	fp8	100.0%
Modalcache modal	$0.30	$1.20	$0.03	1M	944K	—	100.0%
BaseTencache baseten	$0.30	$1.20	$0.007	1M	262K	—	100.0%
Parasailcache parasail/fp8	$0.30	$1.20	$0.006	1M	944K	fp8	100.0%
Fireworkscache fireworks	$0.30	$1.20	$0.006	1M	944K	—	100.0%
Venicecache venice/fp8	$0.30	$1.20	$0.0075	1M	131K	fp8	99.9%
Fireworkscache fireworks/us	$0.45	$1.80	$0.009	1M	944K	—	100.0%
BaseTencache baseten/fast	$0.60	$2.40	$0.014	1M	131K	—	58.6%

Supported API Parameters

Parameters accepted by this model when called through ChatOSS or OpenRouter.

frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_pparallel_tool_callspresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_atop_ktop_logprobstop_p

Deep-Dive Benchmarks & Teardowns

Independent benchmark analysis and real-world agent billing teardowns featuring DeepSeek V4.1 Flash.

2026-10-27 · 10 min read

MiniMax M3.1 Flash vs. DeepSeek V4.1 Flash 1017: cheaper tokens, higher bill

Both list at $0.15/$0.60 per million tokens, and MiniMax wins the business-workflow benchmarks. But on vals.ai's Vibe Code Bench v1.1, DeepSeek's October 17 checkpoint scores 87.73% at $0.58 per test while M3.1 Flash scores 73.94% at $1.15 — because the cheaper token burns 66.86M of them per task. Here is the independent evidence and the cache-aware math.

Read article →

2026-09-21 · 11 min read

GLM 5.3 Flash vs. DeepSeek V4.1 Flash: which is better at agentic coding?

Both labs ship a million-token context, MIT weights, and a ~$0.15-per-million price tag. On the independent harnesses that have actually run both models — vals.ai's Vibe Code Bench and Terminal-Bench 2.1, BenchLM's Vibe Code Bench 1-100, and Artificial Analysis' v4.3 index — DeepSeek V4.1 Flash wins agentic coding, and by a wider margin than either vendor's own table suggests.

Read article →

2026-09-10 · 9 min read

DeepSeek V4.1 Flash: Opus 5-tier agentic coding at 1/33 the price

DeepSeek's new ~748B-parameter Flash model (552B backbone + 196B Engram memory) retires V4 Pro, ships native vision, and — on DeepSeek's own max-effort numbers — edges Claude Opus 5 and GPT-5.6 Sol on Terminal-Bench 2.1 and DeepSWE v1.1 while costing $0.15/$0.60 per million tokens. Full benchmark table, pricing math, and where the closed frontier still wins.

Read article →

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