DeepSeek V4 Flash 0731 is ModelCap archive rank #42 (Measured · blended), from the ModelCap Index as of 22 Sept 2026, 02:49 UTC.
DeepSeek V4 Flash 0731 listed OpenRouter input price is $0.04 per 1M tokens and listed output price is $0.64 per 1M tokens, from OpenRouter listed prices as of 22 Sept 2026, 02:49 UTC.
DeepSeek V4 Flash 0731 has a published context limit of 1.3M tokens in the ModelCap catalogue as of 22 Sept 2026, 02:49 UTC.
DeepSeek V4 Flash 0731 has 28 published OpenRouter serving endpoints, from OpenRouter as of 22 Sept 2026, 02:49 UTC.
DeepSeek V4 Flash 0731 weight access is open weights, from ModelCap classification of published repository metadata as of 22 Sept 2026, 02:49 UTC.
Superseded by DeepSeek V4.1 Flash. It no longer holds a current-board position; its all-versions archive rank is #42.
Input
$0.04
per 1M tokens
Output
$0.64
per 1M tokens
Context
1.3M
tokens
Providers
28
endpoints
Gateway spend
—
latest · Vercel share
Providers
Uptime measured over the last 30 minutes
Provider
Input
Output
Context
Quant
Uptime
StreamLakefp8Cheapest
$0.053
$0.158
1M
fp8
99.45%
DeepInfrafp8
$0.06
$0.18
1M
fp8
99.71%
MaMakora
$0.09
$0.195
1M
—
98.58%
DigitalOcean
$0.119
$0.238
1M
—
99.91%
WaWaferfast
$0.10
$0.25
1M
—
100.0%
BaseTenfp8
$0.13
$0.26
1M
fp8
100.0%
CoCoreWeavefp8
$0.13
$0.28
262K
fp8
100.0%
Nebiusfp8
$0.14
$0.28
1M
fp8
93.10%
Together
$0.14
$0.28
1M
—
99.32%
Parasailfp8
$0.14
$0.28
1M
fp8
99.54%
InInceptronfp4
$0.06
$0.30
1M
fp4
100.0%
Venice
$0.175
$0.35
1M
—
99.44%
Morph
$0.142
$0.40
1M
—
95.55%
ReRekafp4
$0.088
$0.528
262K
fp4
99.49%
SRSail Researchfp4
$0.038
$0.55
1M
fp4
99.87%
M2Mancer 2fp8
$0.20
$0.60
1M
fp8
99.21%
Relacefp4
$0.04
$0.64
1M
fp4
99.77%
Fireworks
$0.22
$0.66
1M
—
97.31%
SiliconFlowfp8
$0.22
$0.66
1M
fp8
98.86%
OpOpenInferencefp8
$0.03
$0.80
1M
fp8
99.13%
GMGMICloudfp8
$0.286
$0.858
1M
fp8
100.0%
NeNextBitfp8
$0.352
$1.06
1M
fp8
97.16%
Alibaba
$0.352
$1.06
1M
—
100.0%
Novitafp8
$0.409
$1.23
1M
fp8
100.0%
PhPhala
$0.44
$1.32
1M
—
100.0%
Baidufp8
$0.44
$1.32
1M
fp8
100.0%
AtlasCloudfp4
$0.44
$1.32
1M
fp4
100.0%
Cloudflare
$0.44
$1.32
1.3M
—
100.0%
Hugging Face Inference Providers
Exact repository identity
Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.
Provider
Input
Output
Context
TTFT
Throughput
Features
deepinfra
live
$0.06
$0.18
1M
1193 ms
19.1 tok/s
tools · structured
baseten
live
$0.13
$0.26
1M
450 ms
189.9 tok/s
tools · structured
together
live
$0.14
$0.28
1M
583 ms
45.1 tok/s
tools
novita
live
$0.44
$1.32
1M
738 ms
124.3 tok/s
tools
featherless-ai
live
—
—
—
—
—
—
fireworks-ai
live
—
—
1M
971 ms
100.4 tok/s
tools · structured
scaleway
live
—
—
—
588 ms
159.9 tok/s
tools · structured
Reported evaluation leads (3)
Not independent measurement
Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.
How this position was produced · fused launch placement
No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.
Fused estimate
76.8 ± 5.7
Independent share
4%
Shrink toward corpus
-1.1
Peer ceiling share
0%
Optimism haircut
None required · cross lab probe, 3 probes
Method
precision-weighted-v1
Channels fused into this model’s launch placement
Channel
Estimate
Share
Publisher corpus prior · not independent
publisher-corpus-prior over 203 held-out anchors
60.7 ± 22.7
6%
Specialist board measurement
1 specialist-board observation at 2.1% support
61.3 ± 27.6
4%
Launch card against resolved peers · not independent
launch card against 2 resolved peers on 7 rows
78.7 ± 6.0
90%
· Launch card row automationbench-public: inside the resolved peer range
· Launch card row deepswe: inside the resolved peer range
· Launch card row dsbench-fullstack: inside the resolved peer range
· Launch card row dsbench-hard: inside the resolved peer range
· Launch card row nl-2-repo: inside the resolved peer range
· Launch card row terminal-bench-2-1: inside the resolved peer range
· Launch card row toolathlon-verified: inside the resolved peer range
Bayesian Evidence Score · measured evidence input only
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
Observed capability
61.3
Evidence status
provisional · 2% mass
General preference
—
Coding
—
Agents & tools
—
Reasoning
61.3
Evidence breadth
3%
Evidence coverage
2%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
76.0
Liquidity (providers × uptime)
99.6
Open reach (HF downloads)
99.1
Surface (context / tools / modalities)
85.0
Freshness
81.8
· OpenRouter popularity #4
· 28 live providers
· HF 30d downloads 4135598
· Catalogue: context 1310720, reasoning, tools
· First seen 2026-07-31
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
Arena preference
No matched Arena rating
This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.
Market Gravity breakdown
Usage55%
76.0
OpenRouter weekly popularity across the full model catalogue.
Liquidity25%
99.6
Independent providers versus the model's open or closed cohort, weighted by uptime.
Open reach15%
99.1
Hugging Face 30-day downloads for open models; neutral for closed models.
Freshness5%
81.8
Time since first public availability, on a six-month half-life.
Specification
Context window
1.3M tokens
Max output
944K tokens
Inputs
Text
Outputs
Text
Tokenizer
DeepSeek
Cached input tokens
$0.016 / 1M
First seen on OpenRouter
31 Jul 2026
Capabilities
Supported: Reasoning
Supported: Tool use
Supported: Structured output
Supported: Response format
Not supported: Moderated
Weights & access
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
How does DeepSeek V4 Flash 0731 rank among AI models?
DeepSeek V4 Flash 0731 is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
How much does DeepSeek V4 Flash 0731 cost per 1M tokens?
DeepSeek V4 Flash 0731 is listed at $0.04 per 1M input tokens and $0.64 per 1M output tokens as of 22 September 2026; the lowest output price among 28 providers is $0.158 on StreamLake. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.40 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
What is the context window of DeepSeek V4 Flash 0731?
DeepSeek V4 Flash 0731 has a published context window of 1.3M tokens (1,310,720) and a maximum output of 944K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.
Is DeepSeek V4 Flash 0731 open-weight?
Open weights (mit). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is deepseek-ai/DeepSeek-V4-Flash-0731 on Hugging Face.
Which API providers serve DeepSeek V4 Flash 0731?
28 providers serve DeepSeek V4 Flash 0731 through OpenRouter as of 22 September 2026: OpenInference, Sail Research, Relace, StreamLake, DeepInfra and Inceptron and 22 more. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Which benchmarks has DeepSeek V4 Flash 0731 been evaluated on?
DeepSeek V4 Flash 0731 has published results on 1 public board tracked by ModelCap as of 22 September 2026: ARC-AGI-2 61.4% (#53 of 214). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.
When was DeepSeek V4 Flash 0731 released?
DeepSeek V4 Flash 0731 first appeared in the catalogue on 31 Jul 2026. It has since been superseded by DeepSeek V4.1 Flash. Rank and price movements since then are recorded on the site's changes feed.