TL;DRDeepSeek V4.1 Flash 1017 by DeepSeek scores 65.66 overall, costs $0.30 per 1M input tokens and $1.20 per 1M output tokens, and carries a context window of 1M tokens — observed 2026-10-23.
Canonical iddeepseek-v4-1-flash
Access typeOpen Weight
Blended $/1M$0.5275% input / 25% output
Capability shape
Seven axes from the ranking source. A missing axis is drawn as a gap.
Capability evidence
Multimodal & Grounded77.9 Instruction FollowingUnavailable Runtime service evidence
Measured values with the date they were observed. Nothing is inferred from a sibling model or a provider claim.
Time to first token: latency to the first answer chunk (Artificial Analysis, via BenchLM). Reasoning models include thinking time, so values can run to tens or hundreds of seconds.
Evidence key: Observed
Runtime measurements| Measurement | Value | Observed | Last good | Evidence |
|---|
| Time to first token | 10.66 s | 2026-10-23 | 2026-10-23 | |
| Throughput | 209 tok/s | 2026-10-23 | 2026-10-23 | |
Regional or per-endpoint measurements appear only when the API supplies them; none are modelled here.
Endpoint and price matrix
Every published price component, including cache reads and writes.
Price components| Component | USD | Evidence |
|---|
| Input / 1M tokens | $0.30 | |
| Output / 1M tokens | $1.20 | |
| Cache read / 1M tokens | $0.006 | |
| Cache write / 1M tokens | Unavailable | |
| Blended / 1M (75% input / 25% output) | $0.52 | |
| Cost per successful task (LiveBench) | Unavailable | |
Self-hosted listingDeepSeek's pricing page read October 17, 2026 lists `deepseek-flash` with model version DeepSeek-V4.1-Flash-1017 at the same peak and off-peak rates, and DeepSeek's October 17, 2026 changelog says the upgrade leaves the API calling method and pricing unchanged (https://api-docs.deepseek.com/updates). DeepSeek's pricing page checked September 10, 2026 lists `deepseek-flash` (model version DeepSeek-V4.1-Flash) with peak and off-peak rates, effective 04:00 UTC on September 10, 2026. The stored values are the peak rates: $0.30 cache-miss input / $0.006 cache-hit input / $1.20 output per million tokens. Off-peak rates are half of peak: $0.15 / $0.003 / $0.60. Peak hours are 01:00-04:00 and 06:00-10:00 UTC, Monday through Friday; all other hours are off-peak. The page lists a 1M context length, a 384K maximum output, and a 2,500-request concurrency limit. The legacy `deepseek-v4-flash` and `deepseek-v4-flash-vision-exp` IDs route to this model at the same Flash price, and DeepSeek's September 10, 2026 announcement said `deepseek-v4-pro` requests would join them from 04:00 UTC on September 14, 2026. DeepSeek's pricing page, read September 17, 2026, says V4 Pro API service continues after September 14, 2026 with the billing method unchanged, and that DeepSeek will give notice of any change; the September 10 post had not been edited when read the same day (https://api-docs.deepseek.com/news/news260910, https://api-docs.deepseek.com/quick_start/pricing). MIT-licensed weights are also published on Hugging Face for self-hosting.
Workload-aware monthly cost example
10 conversations per day × 8 messages × 22 active days, 1200 input and 400 output tokens per message, no cache. This uses the same calculator as the cost simulator, so an unavailable applicable rate makes the example unavailable too.
Modelled monthly cost$1.48
Modelled tokens2.82M
Benchmark record
51 matched benchmark rows with their published value, unit, and provenance.
Lifecycle and limitations log
Lifecycle events the source associates with this model, plus what this profile does not claim.
No lifecycle event references this model.That is not evidence the model has no lifecycle plan — only that this source published none.
What this profile does not claimValues are reproduced exactly as their sources published them, in the units those sources declared; none are converted, interpolated, or averaged across providers. Any field marked unavailable was attempted and not returned — the attempt timestamp is in each badge. Last attempted fetch for this model’s score: 2026-10-23 13:17 UTC.
ModelScale