Source: https://ailoot.ai/models/en/deepseek-deepseek-v4-1-flash-u003a-batch/
Canonical: https://ailoot.ai/models/en/deepseek-deepseek-v4-1-flash-u003a-batch/
Language: en

# DeepSeek: DeepSeek V4.1 Flash (batch)

[Markdown](https://ailoot.ai/models/en/deepseek-deepseek-v4-1-flash-u003a-batch/index.md) · [JSON](https://ailoot.ai/models/en/deepseek-deepseek-v4-1-flash-u003a-batch/facts.json)

## [DeepSeek: DeepSeek V4.1 Flash (batch)](https://ailoot.ai/models/en/deepseek-deepseek-v4-1-flash-u003a-batch/)

DeepSeek V4.1 Flash is a multimodal model for text and image analysis, coding and agentic work with a long context window.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `deepseek/deepseek-v4.1-flash:batch`](https://ailoot.ai/models/en/deepseek-deepseek-v4-1-flash-u003a-batch/#method-0)

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

#### Joint processing of text and images

DeepSeek V4.1 Flash is a natively multimodal model: a visual encoder converts an image into a representation processed together with text. Its output is text. Visual understanding, coding and agentic tasks are provided for, with context reaching one million tokens.

#### Architecture for large inputs

The main network contains 552 billion parameters. The causal encoder and decoder each have 20 layers. Input processing activates 8 billion parameters per token, and generation activates 16 billion. This division is designed for tasks whose input material is significantly larger than the response.

Compressed sparse attention reuses data between layers and limits repeated searches for significant parts of the context. Missing local-attention states are reconstructed from a recent segment. Engram conditional memory contains 196 billion parameters and accesses entries through sparse token-based retrieval. This is a separate memory block, not a new designation for the size of the main network. Each expert layer has one shared expert and 384 routed experts; six routed experts are selected for a token. Modified inter-layer connections and DSpark for speculative decoding are also used.

#### Training and agentic environments

The model was trained from scratch on a multimodal corpus of 45 trillion tokens. Subsequent preparation follows this sequence: training from examples, reinforcement learning, then distillation on the model's own sequences.

DeepSeek scales synthetic task data, working environments and agent trajectories. Preparation connects the task itself, the available environment and how the result is verified; data is filtered, deduplicated and selected by difficulty. This describes the training setup, not automatic access to external tools when using the model.

#### Controllable analytical depth

Reasoning is controlled by an integer from 1 to 100. This continuous scale specifies analytical effort; deep reasoning may require more time and tokens.

#### Continuing the conversation and taking action

The model's format provides for multi-turn dialogue, tool calls, retained reasoning and interleaved text and images. The application executes tools; their results become material for the next step.

The response remains text. Visual capability requires an appropriate input method. Context size and recommended generation length do not establish a universal maximum response size.

**Ailoot Ultra · Batch** `POST /v1/batches` `deepseek/deepseek-v4.1-flash:batch`

[`deepseek/deepseek-v4.1-flash:batch`](https://ailoot.ai/models/en/#m=deepseek%2Fdeepseek-v4.1-flash%3Abatch&route=Ultra&caller=deepseek%2Fdeepseek-v4.1-flash%3Abatch&fmt=batches)

DeepSeek /`deepseek/deepseek-v4.1-flash:batch`

### Overview

DeepSeek V4.1 Flash is a multimodal model for text and image analysis, coding and agentic work with a long context window.

Accepted inputs

Text

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot Ultra · Batch** `POST /v1/batches`

Input types

`text`

Output types

`text`

Output format

inline results\[\].response.body JSON

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`endpoint` | Type`string` | RequirementRequired | Values & limits /v1/chat/completions | Default— |
| Field`model` | Type`string` | RequirementRequired | Values & limits deepseek/deepseek-v4.1-flash:batch | Default— |
| Field`requests` | Type`batch_item[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— |
| Field`requests[].custom_id` | Type`string` | RequirementRequired | Values & limits | Default— |
| Field`requests[].body.messages` | Type`message[]` | RequirementRequired | Values & limits | Default— |
| Field`completion_window` | Type`string` | RequirementOptional | Values & limits 24h | Default— |
| Field`provider` | Type`object\|null` | RequirementOptional | Values & limits | Default— |
| Field`requests[].body.model` | Type`string` | RequirementOptional | Values & limits deepseek/deepseek-v4.1-flash:batch, deepseek/deepseek-v4.1-flash | Default— |
| Field`provider.only` | Type`string[]` | RequirementOptional | Values & limits deepinfra/fp8 | Default— |
| Field`provider.allow_fallbacks` | Type`boolean\|null` | RequirementOptional | Values & limits false, null | Default— |

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractendpoint, model, requests |
| Parameter`material_types` | Contracttext |
| Parameter`representation` | Contractinline requests\[\]; each item has custom\_id and body |
| Parameter`request_endpoint_profile` | Contract/v1/chat/completions |
| Parameter`file_material` | ContractCaller may read actual UTF-8 JSONL locally into requests\[\]. No upload purpose, input\_file\_id or file reference is used. Missing/empty customer material stops preparation before POST. |
| Parameter`serialization_order` | Contractendpoint, model, provider (if supplied), completion\_window (if supplied), requests last |
| Parameter`optional_controls` | Contractprovider.only, provider.allow\_fallbacks, completion\_window |
| Parameter`schema_scope` | ContractText Chat Completions bodies in the documented inline Batch envelope. |

Lifecycle: `asynchronous`

`GET /v1/batches/{operation_id}` · actual original create response.id; same user/key/group

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Not specified When fast mode is selected

Flex mode

Not specified When flex mode is selected

Maximum reasoning effort

Not specified When maximum reasoning effort uses the default adjustment

Explicit cache pricing

Not enabled When explicit cache is requested

#### Ailoot rates

#### Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

| Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge |
| --- | --- | --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.000224** / 1K tokens Output · Output tokens **$0.000672** / 1K tokens Input · Cache read **$0.00000672** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.000224** / 1K tokens Output · Output tokens **$0.000672** / 1K tokens Input · Cache read **$0.00000672** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · Batch

curl · retained fixturePython HTTP · actual customer JSONLPython · save every completed result

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
python3 - <<'PY_REQUEST'
import json
from pathlib import Path
body=json.loads('{"endpoint":"/v1/chat/completions","model":"deepseek/deepseek-v4.1-flash:batch","requests":[{"custom_id":"req-0001","body":{"messages":[{"role":"user","content":"Hello!"}],"max_tokens":16}}]}')
Path("batch-request.json").write_text(json.dumps(body,ensure_ascii=False),encoding="utf-8")
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json
```

```python
import json, os
from pathlib import Path
from urllib.request import Request, urlopen

def prepare_requests(customer_path):
    path = Path(customer_path)
    if not path.is_file(): raise ValueError("Customer JSONL file is missing")
    items = [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]
    if not items: raise ValueError("Customer JSONL contains no requests")
    ids = set()
    for item in items:
        if set(item) != {"custom_id", "body"}: raise ValueError("Each item needs custom_id and body")
        cid = item["custom_id"]
        if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError("custom_id must be nonempty and unique")
        ids.add(cid)
        if not isinstance(item["body"], dict) or not item["body"].get("messages"): raise ValueError("Supply actual text messages")
        supplied_model = item["body"].get("model")
        if supplied_model is not None and supplied_model not in ['deepseek/deepseek-v4.1-flash:batch', 'deepseek/deepseek-v4.1-flash']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"deepseek/deepseek-v4.1-flash:batch", "requests":items}

if __name__ == "__main__":
    material = os.environ.get("AILOOT_BATCH_REQUESTS_JSONL", "")
    if not material: raise SystemExit("Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file")
    body = prepare_requests(material)
    key = os.environ.get("AILOOT_API_KEY", "")
    if not key: raise SystemExit("Set AILOOT_API_KEY")
    request = Request("https://api.ailoot.ai/v1/batches", data=json.dumps(body, ensure_ascii=False).encode("utf-8"), headers={"Authorization":"Bearer " + key, "Content-Type":"application/json"}, method="POST")
    with urlopen(request) as response:
        raw = response.read()
        Path("batch-create-response.json").write_bytes(raw)
        print(raw.decode("utf-8"))
```

```python
import json
from pathlib import Path
raw = Path("batch-status-response.json").read_bytes()
response = json.loads(raw)
if response.get("status") != "completed":
    raise SystemExit("Keep the original operation; read its status without resubmitting")
results = response.get("results")
if not isinstance(results, list) or not results:
    raise SystemExit("Preserve the original response; completed results are missing")
Path("batch-results.jsonl").write_text("".join(json.dumps(item, ensure_ascii=False) + "\n" for item in results), encoding="utf-8")
# Preserve batch-status-response.json with aggregate usage and every result/error.
```

### Receive and save results

#### Ailoot Ultra · Batch

inline results\[\].response.body JSON

- `GET /v1/batches/{operation_id}`

##### Check job status

curl · original operation status

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
BATCH_OPERATION_ID="$(python3 - <<'PY_ID'
import json
from pathlib import Path
from urllib.parse import quote
response = json.loads(Path("batch-create-response.json").read_text(encoding="utf-8"))
operation = response.get("id")
if not isinstance(operation, str) or not operation: raise SystemExit("No actual original operation ID; preserve the response and do not resubmit")
print(quote(operation, safe=""))
PY_ID
)"
curl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID" \
  -H "Authorization: Bearer $AILOOT_API_KEY" -o batch-status-response.json
```

##### Keep all completed results

Keep every complete returned response, file and content part.

Preserve the full original status JSON, every result/custom\_id and complete response or error body. Save completed results\[\] as JSONL without filtering.

##### If the original response needs checking

Preserve the original operation ID. 503 result\_pending\_check has X-Should-Retry:false; never resubmit an unknown original batch.

Response fields

| Field | Type |
| --- | --- |
| Field`results[].custom_id` | Typestring |
| Field`results[].response.body.choices[].message.content` | Typestring\|null |
| Field`results[].error` | Typeobject\|null |
| Field`usage` | Typeobject\|null |
| Field`id` | Typestring |
| Field`model` | Typestring |
| Field`endpoint` | Typestring |
| Field`status` | Typestring |
| Field`request_counts` | Typeobject |
| Field`results[].id` | Typestring |
| Field`results[].response.status_code` | Typeinteger |
| Field`results[].response.request_id` | Typestring |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid documented inline envelope, duplicate keys, item identity, or configured model capabilities conflict. | Next stepCorrect the indicated fields before any new submission. |
| Response401 · `authentication_error` | ConditionInvalid API key. | Next stepUse the authorized Ailoot key. |
| Response403 · `permission_error` | ConditionBatch group unavailable. | Next stepCheck key/group entitlement. |
| Response422 · `invalid_request_error` | ConditionBatch uses balance billing; subscription creation is rejected. | Next stepUse the authorized balance-billed group. |
| Response422 · `price_unavailable` | ConditionBatch input cannot be quoted. | Next stepPreserve response; use documented family input. |
| Response402 · `billing_error` | ConditionBatch reserve unavailable. | Next stepResolve admission before a new request. |
| Response503 · `price_unavailable` | ConditionBatch method price/native rates unavailable. | Next stepPreserve response; do not substitute prices. |
| Response503 · `api_error` | ConditionExact supplier route unavailable. | Next stepPreserve response for route repair. |
| Response503 · `result_pending_check` | ConditionOriginal result requires checking; X-Should-Retry:false. | Next stepKeep original operation\_id/id and read its status; never repeat original POST. |
| Response404 · `not_found` | ConditionBatch status operation absent or owned by another identity. | Next stepUse exact original id and same user/key/group. |

### Aliases

#### Model aliases

**Ailoot Ultra** [`deepseek/deepseek-v4.1-flash:batch`](https://ailoot.ai/models/en/#m=deepseek%2Fdeepseek-v4.1-flash%3Abatch&route=Ultra&caller=deepseek%2Fdeepseek-v4.1-flash%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`deepseek/deepseek-v4.1-flash:batch`](https://ailoot.ai/models/en/#m=deepseek%2Fdeepseek-v4.1-flash%3Abatch&route=Ultra&caller=deepseek%2Fdeepseek-v4.1-flash%3Abatch&fmt=batches)

FAQ · DeepSeek: DeepSeek V4.1 Flash (batch)

What inputs and results are available?

`POST /v1/batches` · `deepseek/deepseek-v4.1-flash:batch`: `text` → `text`

Which fields does the request use?

`POST /v1/batches` · `deepseek/deepseek-v4.1-flash:batch`: `endpoint`, `model`, `requests`, `completion_window`, `provider`

What limits apply?

`POST /v1/batches` · `deepseek/deepseek-v4.1-flash:batch`: `requests.min_items`: `1`

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