deepseek/deepseek-v4-flash
- context · $0.1120 / M input tokens · $0.2240 / M output tokens
DeepSeek V4 Flash is a DeepSeek model route on OurToken for developers who need a cost-efficient option for chat, coding, summarization, long-context prompts, and high-volume assistant workloads.
Pricing
Pay-per-use
No upfront costs, pay only for what you use
API Usage
API Access Guide
Code examples
Use the OurToken API endpoint for this model. The examples below use direct HTTP requests and the recommended endpoint for the model family.
curl https://api.ourtoken.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "deepseek-v4-flash",
"messages": [
{
"role": "user",
"content": "Hello!"
}
],
"max_tokens": 256
}'Chat Completions API Reference
Create a chat response with the OpenAI Chat Completions-compatible endpoint. Use https://api.ourtoken.ai/v1 as the SDK Base URL and POST /chat/completions as the endpoint.
Authorization
| Content-Type | application/json |
| Authorization | Bearer YOUR_API_KEY |
Request Body
| Field | Type | Required | Description |
|---|---|---|---|
| model | string | Required | Model ID to call. |
| messages | array<object> | Required | Conversation messages sent to the model. |
| max_tokens | integer | Optional | Maximum number of output tokens. |
| temperature | number | Optional | Sampling temperature. |
| top_p | number | Optional | Nucleus sampling parameter. |
| stream | boolean | Optional | Whether to return a streaming response. |
| stream_options | object | Optional | Additional options for streaming responses. |
| tools | array<object> | Optional | Tools available to the model. |
| tool_choice | string | object | Optional | Controls how the model selects tools. |
| response_format | object | Optional | Controls structured output, such as JSON object responses. |
Response Body
| Field | Type | Required | Description |
|---|---|---|---|
| id | string | Required | Unique chat completion identifier. |
| object | "chat.completion" | Required | Object type returned by the Chat Completions API. |
| created | integer | Required | Unix timestamp when the response was created. |
| model | string | Required | Model that produced the response. |
| choices | array<object> | Required | Candidate responses returned by the model. |
| choices[].message.role | string | Required | Role of the returned chat message. |
| choices[].message.content | string | Optional | Text content in the returned chat message. |
| choices[].finish_reason | string | Optional | Reason generation stopped. |
| usage | object | Optional | Token usage information for the chat completion. |
| usage.prompt_tokens | integer | Optional | Input token count. |
| usage.completion_tokens | integer | Optional | Output token count. |
| usage.total_tokens | integer | Optional | Total token count. |
| usage.prompt_tokens_details | object | Optional | Breakdown of input token usage. |
| usage.prompt_tokens_details.cached_tokens | integer | Optional | Tokens served from cache. |
Model Introduction
DeepSeek deepseek-v4-flash
DeepSeek V4 Flash is a DeepSeek model route on OurToken for developers who need a cost-efficient option for chat, coding, summarization, long-context prompts, and high-volume assistant workloads.
DeepSeek V4 Flash gives teams a lower-cost DeepSeek V4 route for application work where responsiveness, predictable pricing, and simple API integration matter. Use DeepSeek V4 Flash API when you want to test DeepSeek workflows through the OurToken unified API while keeping model IDs, usage logs, cache costs, and price review in one dashboard.
Why It Looks Great
- 80% of the official DeepSeek V4 Flash reference price for input and output tokens.
- OpenAI-compatible API setup through the same OurToken endpoint used by other supported models.
- Clear cache read and cache write pricing for repeated-context prompts and long conversation workloads.
- Useful for evaluating cost-sensitive chat, coding, summarization, and assistant workflows without separate provider-specific integration.
- Dashboard logs and usage visibility help teams review request cost after launch.
Key Features
- Model ID: deepseek-v4-flash
- Input price: $0.1120 per 1M tokens on OurToken
- Output price: $0.2240 per 1M tokens on OurToken
- Cache read price: $0.0020 per 1M tokens on OurToken
- Cache write price: $0 per 1M tokens on OurToken
- Provider: DeepSeek
Specifications
DeepSeek V4 Flash API Features
Use DeepSeek V4 Flash API for unified DeepSeek V4 API access, transparent DeepSeek V4 Flash API pricing, cache visibility, and production evaluation.
Unified Access
Call DeepSeek V4 Flash API through OurToken's unified endpoint while keeping model access, API key management, and usage history in one place. Use deepseek-v4-flash as the model ID and reuse OpenAI-compatible request patterns for chat, coding, and agent workflows.
Pricing Clarity
Review DeepSeek V4 Flash pricing before rollout. OurToken lists $0.1120 input and $0.2240 output per 1M tokens, so teams can estimate the DeepSeek V4 Flash price for chat, coding, and high-volume assistant traffic before scaling production usage.
Cache Costs
Separate cache behavior from normal prompt spend with explicit cache pricing. DeepSeek V4 Flash API cache read is listed at $0.0020 per 1M tokens on OurToken, while cache write is $0 for repeated-context workloads and long prompt reuse.
Flash Workloads
Use the Flash route when responsiveness and cost control matter for production chat, summarization, coding notes, and lightweight agent tasks. Competitor material positions the model for fast inference and high-throughput workloads, which teams should validate with their own prompts.
Long Context
Evaluate DeepSeek V4 API workloads that need long context, such as document review, repository notes, support logs, and multi-turn conversations. Test latency, output quality, and cache behavior before making Flash the default route for large prompts.
Benchmark Review
Use DeepSeek V4 Flash benchmark claims as a starting point, not a production guarantee. Compare coding, reasoning, latency, tool use, and token consumption against your own acceptance criteria before scaling traffic to customer-facing workflows.
How to Use DeepSeek V4 Flash API on OurToken
Create an API key, copy deepseek-v4-flash, compare DeepSeek V4 pricing, call the unified endpoint, and monitor real usage.
Create API Key
Create an OurToken API key from the dashboard and store it in a secure server-side environment variable. This gives your backend access to DeepSeek V4 Flash API while keeping credentials out of client code and public repositories.
01Copy Model ID
Use deepseek-v4-flash as the model value in your request body. Keeping the exact model ID in configuration helps developers avoid naming mistakes when comparing DeepSeek V4 API routes across local tests, staging traffic, and production deployments.
02Call Endpoint
Send requests to the OurToken unified API endpoint with your API key, model ID, and prompt payload. Existing OpenAI-compatible chat request patterns can usually be reused after changing the base URL, credential, and model value.
03Compare Pricing
Compare DeepSeek V4 pricing before rollout: OurToken lists $0.1120 input, $0.2240 output, and $0.0020 cache read per 1M tokens. Use those values to estimate DeepSeek V4 Flash price for expected prompt, output, and cache volumes.
04Test Benchmarks
Treat every DeepSeek V4 Flash benchmark claim as a prompt for your own evaluation. Run representative coding, reasoning, summarization, and agent tasks, then compare response quality, latency, tool behavior, token usage, and error handling.
05Monitor Cost
After launch, review history logs for request count, input tokens, output tokens, cache read tokens, and spend. Real usage data helps teams compare DeepSeek V4 Flash pricing against actual traffic instead of relying only on provider listing assumptions.
06DeepSeek V4 Flash API FAQ
Answers about DeepSeek V4 Flash API pricing, DeepSeek V4 API access, cache costs, model ID setup, benchmarks, and Flash versus Pro evaluation.
