DeepSeek V4.1 Flash (batch)
deepseek/deepseek-v4.1-flash:batchDeepSeek 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.
Standard pricing
Run this model at its standard rate. Cheap mode currently has no separate discount.
API routing ceilings, including your 5% Free-plan fee. Included usage applies first, then prepaid credits. Cached tokens and tools can have separate charges.
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Provider price + a transparent platform fee
| Rate | Provider baseline | Free plan · 5% fee | Paid plan · 4% fee |
|---|---|---|---|
| Input / 1M tokens | $0.011 | $0.01155 | $0.01144 |
| Output / 1M tokens | $0.2 | $0.21 | $0.208 |
| API input / 1M tokens | $0.011 | $0.01155 | $0.01144 |
| API output / 1M tokens | $0.2 | $0.21 | $0.208 |
Legacy chat image rates use the catalog baseline. The dedicated image playground shows separate estimates and settles the provider’s metered usage. API rates are current routing ceilings; final API charges use provider-reported cost plus your fee. Cheapest routing compares eligible OpenRouter and Cheaper Inference rates for the same model; savings are not guaranteed. Cached input or other provider charges may differ. Compare all model rates and verified discounts →
How your plan pays for usage
API and playground share one included allowance. Usage including the fee draws from that allowance first, then your prepaid credits. Plans bill monthly; included usage resets weekly: Free $1, Starter $5, Growth $25, Scale $50.
A $1 provider charge becomes $1.05 on Free or $1.04 on a paid plan before included usage is applied. Plan eligibility still applies in the playground.
Free models and limits
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Free includes 20 API requests/minute and 6 playground messages/minute. Paid plans raise these limits. See plan limits.
Before a text API request, Gizmo temporarily reserves included usage and, if necessary, prepaid credit for the model’s full context plus your maximum output. Image jobs reserve twice their displayed estimate. Unused funds return after metering. This hold can exceed the final charge; unconfirmed usage remains marked pending.
Overview
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 output from a 552B-parameter backbone, an asymmetric split that keeps per-token compute low relative to the model's total size. Image understanding is native to the architecture, with visual and text embeddings trained jointly from the start of pre-training rather than added afterward as in the earlier experimental V4 Flash Vision ExpOpens in new tab.
It is suited for coding, terminal, and computer-use agents, along with long-horizon tasks that must run to completion across many steps and long-context analysis. Compressed KV caching cuts cache memory to roughly a quarter of the previous Flash generation, significantly reducing costs on agentic workloads. DeepSeek positions it as the cost-efficient tier of the V4.1 family and reports that it exceeds V4 ProOpens in new tab on performance, speed, and task completion time.
Benchmarks
Artificial Analysis indices independent, 0–100
Base Model from the model card
| Benchmark (Metric) | # Shots | DeepSeek-V4-Flash-Base | DeepSeek-V4-Pro-Base | DeepSeek-V4.1-Flash-Base |
|---|---|---|---|---|
| Architecture | — | MoE | MoE | MoE |
| # Backbone Params | — | 284B | 1.6T | 552B |
| # Activated Params | — | 13B | 49B | 8B / 16B |
| World Knowledge | ||||
| AGIEval (EM) | 3–5-shot | 83.9 | 84.4 | 83.4 |
| MMLU-Pro (EM) | 5-shot | 68.3 | 73.5 | 74.1 |
| C-Eval (EM) | 5-shot | 92.1 | 93.1 | 92.1 |
| MultiLoKo (LLM-Judge) | 5-shot | 42.6 | 50.9 | 45.5 |
| SimpleQA-Verified (EM) | 25-shot | 30.1 | 55.2 | 42.3 |
| SuperGPQA (EM) | 5-shot | 46.5 | 53.9 | 53.1 |
| Language & Reasoning | ||||
| BBH (EM) | 3-shot | 86.9 | 87.5 | 86.1 |
| BBEH (EM) | 1-shot | 25.4 | 29.8 | 27.2 |
| DROP (F1) | 1-shot | 88.6 | 88.7 | 87.9 |
| HellaSwag (EM) | 0-shot | 85.7 | 88.0 | 87.2 |
| Code & Math | ||||
| BigCodeBench (Pass@1) | 3-shot | 56.8 | 59.2 | 60.6 |
| HumanEval (Pass@1) | 0-shot | 69.5 | 76.8 | 79.4 |
| GSM8K (EM) | 8-shot | 90.8 | 92.6 | 93.0 |
| MATH (EM) | 4-shot | 57.4 | 64.5 | 61.1 |
| MGSM (EM) | 8-shot | 85.7 | 84.4 | 80.2 |
| Long Context | ||||
| LongBench-V2 (EM) | 1-shot | 44.7 | 51.5 | 45.2 |
| Multimodal | ||||
Comparison with frontier models (Max reasoning effort) from the model card
| Benchmark (Metric) | Opus-5.0 | GPT-5.6 Sol | K3 | GLM-5.3 | DS-V4-Pro | DS-V4-Flash | DS-V4.1-Flash |
|---|---|---|---|---|---|---|---|
| Reasoning | |||||||
| GPQA Diamond (Pass@1) | 93.4 | 94.1 | 92.9 | 88.1 | 92.4 | 89.9 | 90.9 |
| HLE (Pass@1) | 56.3 | 44.5 | 43.5 | 42.0† | 42.7† | 37.8† | 36.8 (39.1†) |
| Codeforces (Rating) | — | — | — | — | 3348 | 3289 | 3471 |
| MathArena Apex (Pass@1) | — | — | 65.6 | — | 65.3 | 58.6 | 65.6 |
| Agentic | |||||||
| Terminal-Bench 2.1 (Pass@1) | 89.1 | 88.8 | 88.3 | 88.2 | 87.9 | 82.7 | 90.6 |
| Terminal-Bench 3.0 (Pass@1) | 43.3 | 34.4 | 17.7 | 28.3 | 11.8 | 7.6 | 30.0 |
| Terminal-Bench 4.0 (Pass@1) | 51.8 | 39.9 | 12.6 | 37.9 | 12.4 | 7.0 | 31.2 |
| DeepSWE v1.1 (Resolved) | 74.0 | 73.0 | 67.5 | 66.9 | 62.7 | 54.4 | 74.2 |
| ProgramBench (Almost@1) | 37.0 | 23.0 | 17.5 | 19.0 | 15.5 | — | 20.3 |
| NL2Repo-Bench (Score) | 75.3 | 56.8 | 58.0 | 58.0 | 61.5 | 54.2 | 64.0 |
| CyberGym (Pass@1) | — | 84.5 | 80.0 | 84.5 | 83.3 | 76.7 | 88.1 |
| SEC-Bench Pro (Pass@1) | — | 74.3 | — | — | 56.4 | 30.9 | 62.8 |
| ExploitGym (Pass@1) | 22.1 | 33.7 | — | 15.0 | 5.4 | 1.8 | 15.3 |
| HLE w/ tools (Pass@1) | 63.6 | — | 59.8 | 62.5 | 60.0 | 51.5 | 63.9 |
| AutomationBench (Pass@1) | 50.3 | 45.8 | 46.7 | 48.8 | 43.2 | 37.7 | 54.8 |
| Agent's Last Exam (Pass@1) | 28.6 | 26.7 | 27.6 | 28.5 | 25.7 | 25.2 | 31.8 |
| Chartography w/ tools (Pass@1) | 84.0 | 79.9 | 68.1 | — | — | — | 78.9 |
| BabyVision w/ tools (Pass@1) | 94.1 | 88.9 | 85.7 | — | — | — | 89.6 |
| ZeroBench-main w/ tools (Pass@5) | 52.0 | 53.0 | 41.0 | — | — | — | 49.0 |
Performance across agent scaffolds (DeepSWE v1.1 and Terminal-Bench 2.1, Max reasoning effort) from the model card
| Benchmark (Metric) | Claude Code | Codex | OpenCode | Pi | mini-SWE | DSH Minimal | DSH Standard |
|---|---|---|---|---|---|---|---|
| DeepSWE v1.1 (Resolved) | 69.8 | 65.6 | 65.5 | 66.2 | 74.2 | 72.6 | 70.5 |
| Terminal-Bench 2.1 (Pass@1) | 88.0 | 84.1 | 85.0 | 86.1 | 90.3 | 90.6 | 85.8 |
Capabilities
Reasoning is on by default with effort levels max · high · low (default high).
Sampling controls: temperature, top_p, top_k, min_p, max_tokens, frequency_penalty, presence_penalty, repetition_penalty.
Pricing on Gizmo
These are provider baseline rates before Gizmo’s 5% Free-plan or 4% paid-plan fee. Your included usage covers charges first; overage uses prepaid credits. See the fee-inclusive comparison above.
Provider baseline rates
- Input
- $0.011 / 1M
- Cached input
- $0.0034 / 1M
- Output
- $0.2 / 1M
Examples before the platform fee
- Typical chat turn
- $0.00012 2k in · 500 out
- $1 of input
- ≈ 90.91M tokens
- $1 of output
- ≈ 5M tokens
- Full context, once
- $0.0115
Providers and pricing
One way to run DeepSeek V4.1 Flash (batch) on Gizmo.
| Provider | Route | Input / 1M | Output / 1M | Context | Uptime 24h |
|---|---|---|---|---|---|
| Morph · fp8Lowest price | OpenRouter | $0.011 | $0.20 | 1.05M | — |
Rates are each provider’s, per million tokens, before Gizmo’s 5% (Free) or 4% (paid) fee. “Cheapest” routing starts at the top of this list; “Fastest” starts with the model’s maker.
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