Inference availability
Providers Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.
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Specification
Capabilities Recorded from the source catalog and provider listings.
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Reasoning
Unknown
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Tool calling
Unknown
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Structured output
Unknown
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Attachments
Unknown
×
Vision input
No
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Open weights
Unknown
Model family Not documented
Knowledge cutoff Not documented
License Not documented
Release date Not documented
Model ID deepseek/deepseek-v4-flash-0731:batch
Published evaluations
Benchmarks Every result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.
Benchmark registry
Benchmark profile
Coding IndexCoding Index
Agentic IndexAgentic Index
IntelligenceIntelligence Index
Design Arena: w…Design Arena: website
Design Arena: c…Design Arena: codecategories
Design Arena: g…Design Arena: gamedev
Design Arena: d…Design Arena: dataviz
Design Arena: u…Design Arena: uicomponent
This model — Coding Index: 69.1 index (77.6th percentile)
This model — Agentic Index: 41.7 index (80.8th percentile)
This model — Intelligence Index: 34.5 index (66.9th percentile)
This model — Design Arena: website: 1251 elo (64.0th percentile)
This model — Design Arena: codecategories: 1245 elo (61.1th percentile)
This model — Design Arena: gamedev: 1234 elo (62.3th percentile)
This model — Design Arena: dataviz: 1197 elo (48.2th percentile)
This model — Design Arena: uicomponent: 1251 elo (61.8th percentile)
Each axis is this model's percentile among the 8 benchmarks it has published results for, measured against every other model with a score on that same benchmark. Percentiles are used because benchmarks do not share a scale — a 60 on one is not a 60 on another. Hover any point for the raw score.
Coding Index
#46 of 205
2.7
median 49.3
81.6
Agentic Index
#37 of 193
0.1
median 19.7
58.0
Intelligence Index
#63 of 192
3.8
median 25.6
55.0
Design Arena: website
#63 of 175
762.0
median 1202.0
1359.0
Design Arena: codecategories
#65 of 167
804.0
median 1198.0
1389.0
Design Arena: gamedev
#62 of 166
796.0
median 1193.5
1414.0
Design Arena: dataviz
#85 of 165
871.0
median 1198.0
1366.0
Design Arena: uicomponent
#61 of 161
782.0
median 1205.0
1394.0
Design Arena: 3d
#60 of 157
865.0
median 1190.0
1426.0
Design Arena: svg
#40 of 116
992.0
median 1188.0
1352.0
Design Arena: asciiart
#87 of 99
1018.0
median 1186.0
1386.0
Each strip shows every published score for that benchmark, with this model marked. The lighter shape behind the ticks is the density of results, and the dashed line is the median.
Cost against capability
Price and performance Listed input price plotted against Coding Index, the benchmark with the widest published coverage that this model appears in.
0
43
86
$0.01
$0.1
$1
$10
Qwen: Qwen3.6 Plus — $0.325/M, score 54.5
Qwen: Qwen3 Next 80B A3B Thinking — $0.15/M, score 17.4
OpenAI: GPT-4 Turbo (batch) — $5/M, score 21.5
Mistral: Ministral 3 8B 2512 (batch) — $0.075/M, score 9.7
OpenAI: o3 Mini High (batch) — $0.55/M, score 16.3
Qwen: Qwen3.8 Max (0902) — $2/M, score 71.8
Gemini 3.5 Flash — $1.5/M, score 70.1
Z.ai: GLM 5.3 Flash (batch) — $0.075/M, score 71.5
Gemma 3 12B IT — $0.05/M, score 5.8
GPT-4.1 mini — $0.4/M, score 20.2
DeepSeek V4 Pro — $0.435/M, score 59.4
Claude Sonnet 5 — $2/M, score 71.5
Mistral: Ministral 3 8B 2512 — $0.15/M, score 9.7
Gemini 3.1 Flash Lite Preview — $0.25/M, score 34.7
OpenAI: o1 (batch) — $7.5/M, score 39.7
Anthropic: Claude Fable 5.1 (batch) — $5/M, score 81.6
Gemini 3.7 Flash — $0.75/M, score 76.1
LongCat-2.0 — $0.3/M, score 45.3
Z.ai: GLM 5.1 — $0.966/M, score 55.8
Anthropic: Claude Opus 4.8 (batch) — $2.5/M, score 74.3
Mistral: Mistral Large 3 2512 — $0.5/M, score 20.1
DeepSeek V3.2 — $0.18/M, score 44.2
Anthropic: Claude Opus 4.7 — $5/M, score 73.6
Google: Gemini 3.5 Flash (batch) — $0.75/M, score 70.1
OpenAI: GPT-5.4 Nano (batch) — $0.1/M, score 56.1
Inception: Mercury 2 — $0.25/M, score 31.1
OpenAI: GPT-4o-mini (batch) — $0.075/M, score 11.4
Qwen: Qwen3.5-9B (batch) — $0.17/M, score 28.7
Gemini 3.6 Flash — $0.75/M, score 69.2
Gemma 4 26B A4B IT — $0.042/M, score 39.3
Claude Fable 5 — $10/M, score 76.5
Gemma 4 31B IT — $0.09/M, score 43.4
Z.ai: GLM 5.3 Flash — $0.15/M, score 71.5
OpenAI: GPT-3.5 Turbo (batch) — $0.25/M, score 10.7
Gemma 3 27B IT — $0.08/M, score 10.1
MiniMax: MiniMax M3 — $0.3/M, score 58.6
DeepSeek: DeepSeek V4 Pro 0813 (batch) — $0.66/M, score 68.8
Thinking Machines: Inkling Small (batch) — $0.5/M, score 52.9
Anthropic: Claude Fable 5.1 — $10/M, score 81.6
Google: Gemma 4 31B (batch) — $0.39/M, score 43.4
Qwen: Qwen3.8 2.4T A95B (batch) — $2/M, score 71.9
Mistral: Devstral 2 2512 — $0.4/M, score 31.3
MoonshotAI: Kimi K2.7 Code (batch) — $0.95/M, score 60.8
Inkling — $1.87/M, score 52.1
OpenAI: gpt-oss-20b (batch) — $0.05/M, score 20.7
Muse Spark 1.1 — $1.25/M, score 71.3
MiMo-V2.5 — $0.14/M, score 56.8
Google: Gemini 3.5 Flash Lite (batch) — $0.15/M, score 49.3
Kimi K2 Thinking — $0.4/M, score 21.0
Mistral: Mistral Medium 3.5 (batch) — $0.75/M, score 46.9
GPT-5.6 Luna — $0.2/M, score 71.4
Qwen: Qwen3.8 Max (0803) — $2/M, score 68.9
Mistral: Mistral Medium 3.1 (batch) — $0.2/M, score 20.5
GPT-5.1 — $1.25/M, score 49.4
Qwen: Qwen3.8 27B — $0.42/M, score 68.1
Google: Gemini 3.8 Flash (batch) — $0.375/M, score 76.3
Google: Gemini 3.7 Flash (batch) — $0.375/M, score 76.1
Mistral: Mistral Small 4 (batch) — $0.075/M, score 26.6
inclusionAI: Ling 3.0 Flash VL — $0.06/M, score 57.0
Z.ai: GLM 5.3 (batch) — $0.7/M, score 74.8
DeepSeek: DeepSeek V4 Flash 0731 (batch) — $0.11/M, score 69.1
OpenAI: GPT-5.5 (batch) — $2.5/M, score 74.9
MoonshotAI: Kimi K3 (batch) — $3/M, score 76.2
Inkling Small — $0.45/M, score 52.9
Anthropic: Claude Sonnet 5 (batch) — $1/M, score 71.5
Anthropic: Claude Fable 5 (batch) — $5/M, score 76.5
Nemotron 3 Super 120B A12B — $0.2/M, score 37.7
IBM: Granite 4.2 8B — $0.06/M, score 22.4
OpenAI: GPT-5 (batch) — $0.625/M, score 37.8
Google: Gemini 2.5 Pro (batch) — $0.625/M, score 33.3
GPT OSS 120B — $0.03/M, score 30.4
OpenAI: gpt-oss-120b (batch) — $0.15/M, score 30.4
OpenAI: GPT-4.1 Mini (batch) — $0.2/M, score 20.2
OpenAI: GPT-4.1 Nano (batch) — $0.05/M, score 11.1
SpaceXAI: Grok 4.6 — $2/M, score 76.8
DeepSeek-R1 — $0.7/M, score 24.6
DeepSeek: DeepSeek V3.1 Terminus — $0.27/M, score 43.5
OpenAI: GPT-6 Astra (batch) — $5/M, score 76.9
OpenAI: GPT-5.6 Terra (batch) — $1/M, score 76.7
Gemini 3.1 Pro Preview — $2/M, score 68.8
Gemma 3 4B IT — $0.04/M, score 2.7
DeepSeek V4 Pro 0813 — $0.442/M, score 68.8
Z.ai: GLM 5.2 (batch) — $0.7/M, score 68.8
Google: Gemini 3.6 Flash (batch) — $0.375/M, score 69.2
GPT-6 Astra — $10/M, score 76.9
Nemotron 3 Nano 30B A3B — $0.05/M, score 14.4
Z.ai: GLM 5.3 — $1.4/M, score 74.8
Anthropic: Claude Opus 4.8 — $5/M, score 74.3
SpaceXAI: Grok 4.3 — $1.25/M, score 42.2
GPT-5.6 Terra — $2/M, score 76.7
MiniMax: MiniMax M3 (batch) — $0.3/M, score 58.6
Gemini 3.8 Flash — $0.75/M, score 76.3
NVIDIA: Nemotron 3 Ultra (batch) — $0.6/M, score 49.3
MiniMax: MiniMax M2.7 — $0.3/M, score 52.6
Kimi K2.6 — $0.95/M, score 61.8
Kimi K3 — $3/M, score 76.2
Anthropic: Claude Sonnet 4.5 (batch) — $1.5/M, score 52.1
Claude Opus 5 — $5/M, score 78.0
Claude Opus 5 (batch) — $2.5/M, score 78.0
SpaceXAI: Grok 4.5 — $2/M, score 72.4
Mistral: Mistral Large 3 2512 (batch) — $0.25/M, score 20.1
OpenAI: GPT-5.1 (batch) — $0.625/M, score 49.4
Anthropic: Claude Opus 4.7 (batch) — $2.5/M, score 73.6
Anthropic: Claude Sonnet 4.5 — $3/M, score 52.1
Google: Gemini 3.1 Pro Preview (batch) — $1/M, score 68.8
Mistral: Mistral Medium 3.1 — $0.4/M, score 20.5
MiMo-V2.5-Pro — $0.435/M, score 60.2
Thinking Machines: Inkling (batch) — $1/M, score 52.1
GPT-5.5 — $5/M, score 74.9
OpenAI: GPT-5.4 (batch) — $1.25/M, score 71.1
Anthropic: Claude Sonnet 4.6 — $3/M, score 63.0
Anthropic: Claude Sonnet 4.6 (batch) — $1.5/M, score 63.0
DeepSeek V4 Flash 0731 — $0.05/M, score 69.1
GPT-5 — $1.25/M, score 37.8
Anthropic: Claude Haiku 4.5 (batch) — $0.5/M, score 43.9
OpenAI: GPT-5 Mini (batch) — $0.125/M, score 15.6
Gemini 2.5 Pro — $1.25/M, score 33.3
inclusionAI: Ling 3.0 Flash — $0.021/M, score 50.6
Qwen: Qwen3.7 Plus — $0.32/M, score 55.9
SpaceXAI: Grok 4.3 (batch) — $1/M, score 42.2
Nemotron 3 Ultra 550B A55B — $0.5/M, score 49.3
Anthropic: Claude Sonnet 4 — $3/M, score 37.6
OpenAI: GPT-5.6 Luna (batch) — $0.1/M, score 71.4
OpenAI: GPT-5.4 Mini (batch) — $0.375/M, score 56.1
GPT OSS 20B — $0.02/M, score 20.7
Qwen: Qwen3.8 2.4T A95B — $2/M, score 71.9
GPT-4 Turbo — $10/M, score 21.5
OpenAI: GPT-5.6 Sol (batch) — $1/M, score 77.4
o1 — $15/M, score 39.7
GPT-5.4 mini — $0.75/M, score 56.1
Z.ai: GLM 4.6 — $0.43/M, score 45.8
GPT-5 Mini — $0.25/M, score 15.6
GPT-4 — $30/M, score 13.1
Kimi K2.7 Code — $0.95/M, score 60.8
GPT-4o (2024-05-13) — $5/M, score 24.2
Gemini 3.5 Flash Lite — $0.3/M, score 49.3
Hy3 preview — $0.066/M, score 58.8
Muse Spark 1.2 — $1.25/M, score 72.2
DeepSeek V4 Flash — $0.15/M, score 52.0
Nemotron 3.5 Lightning 30B A3B — $0.05/M, score 26.8
GPT-5.6 Sol — $4/M, score 77.4
GPT-4.1 nano — $0.1/M, score 11.1
GPT-5.4 — $2.5/M, score 71.1
GPT-4o mini — $0.15/M, score 11.4
GPT-5.4 nano — $0.2/M, score 56.1
GPT-3.5-turbo — $0.5/M, score 10.7
Solar Pro 4 — $0.3/M, score 52.7
Kimi K2.5 — $0.3/M, score 46.8
Trinity Large Thinking — $0.25/M, score 25.8
Qwen: Qwen3 30B A3B Thinking 2507 — $0.2/M, score 12.1
Z.ai: GLM 5.2 — $0.966/M, score 68.8
Qwen: Qwen3.7 Max — $1.475/M, score 66.0
SpaceXAI: Grok Build 0.1 — $1/M, score 51.5
Qwen: Qwen3.6 35B A3B — $0.1/M, score 41.9
Qwen: Qwen3.6 27B — $0.3/M, score 53.7
inclusionAI: Ling-2.6-flash — $0.01/M, score 25.3
Mistral: Mistral Small 4 — $0.15/M, score 26.6
Kwaipilot: KAT-Coder-Pro V2 — $0.3/M, score 59.5
Qwen: Qwen3.5-9B — $0.1/M, score 28.7
Qwen: Qwen3.5-35B-A3B — $0.312/M, score 37.0
Qwen: Qwen3.5-122B-A10B — $0.26/M, score 45.7
Upstage: Solar Pro 3 — $0.15/M, score 16.2
Z.ai: GLM 4.7 — $0.4/M, score 45.3
Amazon: Nova 2 Lite — $0.3/M, score 23.0
Mistral: Ministral 3 3B 2512 — $0.1/M, score 4.8
Google: Gemma 3n 4B — $0.06/M, score 3.2
Meta: Llama 4 Maverick — $0.2/M, score 16.3
OpenAI: o3 Mini High — $1.1/M, score 16.3
Meta: Llama 3.3 70B Instruct — $0.1/M, score 11.9
Meta: Llama 3.1 8B Instruct — $0.05/M, score 5.4
Nex AGI: Nex-N2-Pro — $0.25/M, score 59.1
Mistral: Mistral Medium 3.5 — $1.5/M, score 46.9
inclusionAI: Ring-2.6-1T — $0.075/M, score 42.8
IBM: Granite 4.1 8B — $0.05/M, score 9.5
Qwen: Qwen3.5 397B A17B — $0.55/M, score 48.2
Qwen: Qwen3 Coder Next — $0.12/M, score 36.2
Mistral: Ministral 3 14B 2512 — $0.2/M, score 14.4
Anthropic: Claude Haiku 4.5 — $1/M, score 43.9
Qwen: Qwen3 235B A22B Thinking 2507 — $0.23/M, score 22.1
Qwen: Qwen3 8B — $0.117/M, score 9.0
Qwen: Qwen3 14B — $0.227/M, score 13.8
Qwen: Qwen3 32B — $0.08/M, score 15.3
Meta: Llama 4 Scout — $0.1/M, score 8.2
DeepSeek: DeepSeek V3 0324 — $0.25/M, score 21.2
Cohere: Command A — $2.5/M, score 27.8
Step 3.7 Flash — $0.185/M, score 39.6
DeepSeek: DeepSeek V4 Flash 0731 (batch)
Input price per million tokens (log scale)
Index
The stepped line is the efficient frontier: at each price, the best score available for that money or less. A model sitting on it is not being beaten by anything cheaper. Price is log-scaled because listed rates span four orders of magnitude. Only models with both a listed price and a score on this benchmark can appear.
Catalog activity
Change log Field-level changes detected between successful source imports.
Full change log
Sep 08, 2026 Price Completion 0.28 → 0.33
Sep 08, 2026 Price Prompt 0.14 → 0.11
Provenance
Sources & verification Every figure on this page traces back to one of these records.
Methodology
Last verified Sep 11, 2026
Status Source-linked
Confidence Medium
Catalog source OpenRouter
Public API
Use this record Fetch the complete source-linked model record. No key, no account, no rate-limited tier.
API documentation
Endpoint Copy
GET https://model.kyssta.lol/api/v1/models/deepseek/deepseek-v4-flash-0731:batchcurl Copy
curl "https://model.kyssta.lol/api/v1/models/deepseek/deepseek-v4-flash-0731:batch"
Common questions
Frequently asked questions Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.
What is DeepSeek: DeepSeek V4 Flash 0731 (batch)?
DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows. It is published by DeepSeek and catalogued here from OpenRouter.
What is the context length of DeepSeek: DeepSeek V4 Flash 0731 (batch)?
DeepSeek: DeepSeek V4 Flash 0731 (batch) accepts up to 1.04858M tokens of context and returns up to 943.718K output tokens.
