Short answer: “DeepSeek-V3 3” is not a confirmed model name
The official materials reviewed document DeepSeek-V3 and DeepSeek-V3-Base. They do not establish a separate DeepSeek-V3.3 release. The extra “3” in the search phrase remains ambiguous, so this guide covers the documented V3 model rather than assuming a V3.3 exists. (DeepSeek-V3 repository)
There is an important production distinction: DeepSeek’s current pricing documentation names deepseek-flash and deepseek-v4-pro. It maps deepseek-flash to DeepSeek-V4.1-Flash-1017—not V3. The documented model names therefore do not establish that V3 is currently available through DeepSeek’s API. (DeepSeek Models & Pricing)
DeepSeek-V3 at a glance
DeepSeek’s repository describes V3 as a Mixture-of-Experts (MoE) model with 671 billion total parameters and 37 billion activated per token. Its downloads table lists a 128K context window for both V3 and V3-Base. These are repository-stated specifications; the 37B activated figure is not the model’s total size. (DeepSeek-V3 repository)
The repository also reports a total Hugging Face download size of 685B, including the main-model weights and a Multi-Token Prediction module. That download-size figure is distinct from the parameters activated for each token. (DeepSeek-V3 README)
What the published evaluations suggest—and what they don’t
The repository’s chat-model results may make V3 worth evaluating for math and coding workloads. Examples include 39.2 on AIME 2024 Pass@1, 90.2 on MATH-500 exact match, and 40.5 on LiveCodeBench Pass@1-CoT. These are the repository’s reported benchmark results, not independent tests of your application. (DeepSeek-V3 README)
The same table offers a counterpoint to any broad claim that V3 is best for every task: on SimpleQA Correct, it reports 24.9 for V3, compared with 38.2 for GPT-4o-0513 and 28.4 for Claude-3.5-Sonnet-1022. That one benchmark does not establish a general factuality ranking, but it is a reason to test factual-answering tasks directly rather than rely on math or coding scores. (DeepSeek-V3 README)
The repository says its chat-model evaluations limited output length to 8K, and that benchmarks with fewer than 1,000 samples were tested multiple times at varying temperatures. It also summarizes Needle In A Haystack performance across context lengths up to 128K, but the captured summary does not provide detailed scores. Neither the benchmark table nor the context-window listing guarantees quality, speed, or reliability on a particular production workload. (DeepSeek-V3 README)
Selection judgment: V3 is a reasonable candidate to test when you have a V3 checkpoint or a provider that explicitly offers it, and your workload aligns with its reported coding or math results. Do not select it on benchmark scores alone. Evaluate representative prompts and outputs, task success, latency, and total cost against your acceptance criteria. For a DeepSeek-hosted API choice, first confirm the live model ID: the current documented offering is not named V3. (DeepSeek Models & Pricing)
Production API: what DeepSeek currently documents
DeepSeek’s current quick-start documentation gives an OpenAI-compatible base URL of https://api.deepseek.com, Bearer API-key authentication, and deepseek-flash as a model name. Its pricing page maps that name to DeepSeek-V4.1-Flash-1017. It also documents a chat-completions example at /chat/completions. Compatibility with an OpenAI-style API is useful, but it does not mean every model name, parameter, or feature is interchangeable. (DeepSeek API quick start)
For example, the documented request shape is:
curl https://api.deepseek.com/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $DEEPSEEK_API_KEY" \
-d '{"model":"deepseek-flash","messages":[{"role":"user","content":"Hello"}]}'
This illustrates the currently documented Flash API call; it is not a V3 request. Before building, check the current model list and documentation for the features your application needs, such as streaming, tool calls, or a specific context/output limit. The model-list endpoint is GET https://api.deepseek.com/models; the API docs say it returns identifiers and metadata such as context window, output limit, modalities, and API capabilities. (DeepSeek model-list endpoint)
Current listed Flash pricing
Pricing documentation reviewed November 10, 2026. The English pricing table displays amounts with $ and lists rates per 1 million tokens for deepseek-flash:
| Token billing category | Off-peak | Peak |
|---|---|---|
| Input, cache miss | $0.15 | $0.30 |
| Input, cache hit | $0.003 | $0.006 |
| Output | $0.60 | $1.20 |
The documentation defines peak hours as 01:00–04:00 and 06:00–10:00 UTC, Monday through Friday, excluding Chinese public holidays. All other hours—including weekends and Chinese public holidays—are off-peak. These are the listed rates for the current Flash API model, not V3 pricing. The English table uses $ but does not separately specify an ISO currency code; confirm the applicable billing terms on the pricing page. DeepSeek says prices may change, so check that page before forecasting spend. (DeepSeek Models & Pricing)
Worked estimate: At off-peak rates, 1 million cache-miss input tokens plus 200,000 output tokens would cost $0.27 before any other applicable charges: $0.15 + (0.2 × $0.60). At peak rates, the same token counts would cost $0.54: $0.30 + (0.2 × $1.20). This example assumes every input token is a cache miss; a workload with cache hits has a different input cost. The applicable rate depends on the documented time band. (DeepSeek Models & Pricing)
The official V3 announcement contains older rates—$0.27 per million cache-miss input tokens, $0.07 per million cache-hit input tokens, and $1.10 per million output tokens—and says they applied “from Feb 8 onwards” without specifying a year. Do not treat that announcement-era snapshot as current pricing. (Introducing DeepSeek-V3)
Bottom line
- If “deepseek-v3 3” means V3.3: the official sources reviewed here do not confirm that model name. Don’t assume the extra “3” identifies a version.
- If you mean the published DeepSeek-V3 model: its reported specifications and benchmark results can justify a workload-specific evaluation, especially for coding or math, but they do not predict your application’s results.
- If you want DeepSeek’s production API now: its current pricing documentation names
deepseek-flashanddeepseek-v4-pro;deepseek-flashmaps to V4.1-Flash-1017, not V3. Verify the model ID, limits, required features, and price before integrating. (DeepSeek Models & Pricing) - If you plan to use another provider, including TokenForgeCloud: verify that provider’s model availability, exact ID, API behavior, and pricing separately. DeepSeek’s documentation does not establish another provider’s offering or terms.
The V3 repository says commercial use is supported, while also making use of the Base and Chat models subject to the Model License. Review the applicable license terms rather than treating that summary as unrestricted permission. (DeepSeek-V3 README)
Sources
Models & Pricing | DeepSeek API Docs
Your First API Call | DeepSeek API Docs