Choose DeepSeek V4 Pro 0813 when a wrong answer costs more than the tokens: knowledge-heavy reasoning, long-context planning, and high-stakes agentic work. Choose DeepSeek V4.1 Flash when the job is a coding agent, terminal or tool use, or anything that needs image input, because it is the cheapest of the three on Novita AI and now scores highest on agentic benchmarks. Choose DeepSeek V4 Flash 0731 only when a text-only workload already matches its behavior and there is no reason to move. All three share a 1,048,576-token context window and the same OpenAI-compatible endpoint on Novita AI, so the choice comes down to price, modality, and where each model scores highest.
DeepSeek V4 Pro vs Flash vs V4.1 Flash: Quick Comparison
| Category | DeepSeek V4 Pro 0813 | DeepSeek V4 Flash 0731 | DeepSeek V4.1 Flash | What it means |
|---|---|---|---|---|
| Best for | Knowledge-heavy reasoning, long-context planning, high-failure-cost answers | Text-only workloads already tuned to Flash behavior | Coding agents, tool use, and multimodal input | Match the model to the failure cost and the input type |
| Model ID | deepseek/deepseek-v4-pro-0813 | deepseek/deepseek-v4-flash-0731 | deepseek/deepseek-v4.1-flash | Only the model value changes between them |
| Context / max output | 1,048,576 / 393,216 tokens | 1,048,576 / 393,216 tokens | 1,048,576 / 393,216 tokens | Context length is not a deciding factor here |
| Input / output modality | Text to text | Text to text | Text and image to text | Only V4.1 Flash reads images directly |
| Input price (per 1M tokens) | $1.32 | $0.44 | $0.30 | V4.1 Flash is the cheapest input |
| Output price (per 1M tokens) | $3.96 | $1.32 | $1.20 | Pro costs about 3.3x V4.1 Flash on output |
| Cache-read price (per 1M tokens) | $0.044 | $0.028 | $0.006 | Cache-heavy prompts favor V4.1 Flash |
Specs and pricing from the Novita AI model pages, checked October 13, 2026.
What Changed Across the DeepSeek V4 Lineup
The V4 family on Novita AI now holds three current models where it used to hold two, and the older entries have moved on.
The preview-era DeepSeek V4 Pro is superseded by the GA release, listed as deepseek/deepseek-v4-pro-0813. It adds a DSpark speculative-decoding module and ships under an MIT license, and its pricing changed when it went GA, so the preview-era figures in older posts no longer apply. The DeepSeek V4 Pro 0813 GA release guide covers that shift in detail.
The original unsuffixed DeepSeek V4 Flash entry is likewise superseded by the dated deepseek/deepseek-v4-flash-0731 revision, which is the Flash model Novita currently lists.
The newest arrival is DeepSeek V4.1 Flash, the September 2026 successor to V4 Flash. It is the first model in the family to accept image input alongside text, and it uses a causal encoder-decoder design with a smaller KV cache. Its agentic scores move up sharply over V4 Flash; the benchmark section below shows by how much.
The practical effect is that the lineup is no longer “big model versus cheap model.” V4.1 Flash is both cheaper than V4 Flash 0731 and stronger on coding and tool-use tasks, so the real decision is between the agentic tier (V4.1 Flash), the reasoning tier (V4 Pro 0813), and the older text-only Flash that many integrations still point at.
Pricing Comparison on Novita AI
| Model | Input (per 1M tokens) | Cache read (per 1M tokens) | Output (per 1M tokens) |
|---|---|---|---|
| DeepSeek V4 Pro 0813 | $1.32 | $0.044 | $3.96 |
| DeepSeek V4 Flash 0731 | $0.44 | $0.028 | $1.32 |
| DeepSeek V4.1 Flash | $0.30 | $0.006 | $1.20 |
Pricing from the Novita AI pricing page and model pages, checked October 13, 2026.
Pro 0813 stays the premium tier. V4.1 Flash undercuts V4 Flash 0731 on input, output, and cache reads, so the newer model is the cheaper one, which inverts the usual “newest costs most” assumption.
A single workload makes the gap concrete. For 1M input tokens plus 1M output tokens with no cache hits, V4 Pro 0813 costs $5.28, V4 Flash 0731 costs $1.76, and V4.1 Flash costs $1.50. Pro is roughly 3.5x V4.1 Flash for the same token volume.
That does not make V4.1 Flash the default for everything. When a task needs the higher knowledge-reasoning scores that Pro 0813 posts on GPQA Diamond, the extra unit cost can still be cheaper than a wrong answer. Pricing also changes, so check the model pages before committing a cost model to production.
Performance Benchmarks and Developer Takeaways
DeepSeek’s published evaluations put V4.1 Flash ahead of both siblings on agentic coding and tool-use tasks, while V4 Pro 0813 keeps the lead on knowledge-heavy reasoning. Treat the numbers as a starting point for your own evaluation, not a universal ranking.
| Benchmark | DeepSeek V4 Pro 0813 | DeepSeek V4 Flash 0731 | DeepSeek V4.1 Flash |
|---|---|---|---|
| Terminal-Bench 2.1 (Pass@1) | 87.9 | 82.7 | 90.6 |
| Terminal-Bench 3.0 (Pass@1) | 11.8 | 7.6 | 30.0 |
| DeepSWE v1.1 (Resolved) | 62.7 | 54.4 | 74.2 |
| AutomationBench (Pass@1) | 43.2 | 37.7 | 54.8 |
| GPQA Diamond (Pass@1) | 92.4 | 89.9 | 90.9 |
Data from DeepSeek’s DeepSeek-V4.1-Flash model card (maximum reasoning effort), checked October 13, 2026.
The split is the useful part. On agentic benchmarks such as Terminal-Bench 2.1 and 3.0, DeepSWE, and AutomationBench, V4.1 Flash leads by a wide margin, and the gap on Terminal-Bench 3.0 (30.0 versus 11.8 for Pro) is large enough to change whether a long tool-use loop finishes at all. On GPQA Diamond, which leans on knowledge and hard reasoning rather than tool use, Pro 0813 is ahead. V4 Flash 0731 trails on both axes, which is why it now reads as the fallback rather than the budget pick.
Before routing production traffic, run your own prompt set across the models you are considering and compare accepted answers, retry rate, latency, structured-output reliability, and total token cost, not just the headline scores.
How to Access the DeepSeek V4 APIs on Novita AI
All three models are serverless on Novita AI and use the same OpenAI-compatible chat completions endpoint, so switching between them means changing one field: the model value. The base URL and API key stay the same.
Verified model pages:
- DeepSeek V4 Pro 0813 uses
deepseek/deepseek-v4-pro-0813 - DeepSeek V4 Flash 0731 uses
deepseek/deepseek-v4-flash-0731 - DeepSeek V4.1 Flash uses
deepseek/deepseek-v4.1-flash
A minimal request against V4.1 Flash; change the model string to route to another model in the family.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_NOVITA_API_KEY",
base_url="https://api.novita.ai/openai",
)
response = client.chat.completions.create(
model="deepseek/deepseek-v4.1-flash",
messages=[{"role": "user", "content": "Summarize the tradeoffs between the DeepSeek V4 models."}],
max_tokens=1024,
temperature=0.7,
)
print(response.choices[0].message.content)V4.1 Flash also accepts image content in the same message structure. Check the Novita AI chat completions reference for the exact image-part format before sending production traffic.
Best Use Cases: A Three-Way Routing Decision
| If your workload… | Choose | Why |
|---|---|---|
| Needs image, screenshot, or document-page input | DeepSeek V4.1 Flash | The only model in the family that reads images |
| Runs coding agents, terminal automation, or multi-step tool use | DeepSeek V4.1 Flash | Leads Terminal-Bench, DeepSWE, and AutomationBench, at the lowest price |
| Is knowledge- or reasoning-heavy with a high failure cost | DeepSeek V4 Pro 0813 | Highest GPQA Diamond score in the family |
| Is high-volume, text-only, and already tuned to V4 Flash behavior | DeepSeek V4 Flash 0731 | Keep it only if your own eval still matches; V4.1 Flash is cheaper otherwise |
| Mixes easy and hard prompts | Route by tier | Send baseline traffic to V4.1 Flash and escalate hard reasoning to V4 Pro 0813 |
Migration Notes
Switching models is a one-line change, but a few checks keep it safe:
- Confirm the current model ID and pricing on the model page before you ship; the family has changed IDs and prices more than once this year.
- Move from the unsuffixed Flash or Pro IDs to the dated
-0731and-0813entries, which are the models Novita currently lists. - If you adopt V4.1 Flash for image input, update your message construction to include image parts.
- Keep the model ID, context limit, and pricing in configuration rather than hardcoded, so you can roll back.
- Run a representative prompt regression set and compare output quality by task type, not only aggregate win rate.
Conclusion
The DeepSeek V4 family on Novita AI is now a three-model lineup with a clear split. DeepSeek V4.1 Flash is the default for coding agents, tool use, and any workload that needs image input: it is the cheapest of the three and the strongest on agentic benchmarks. DeepSeek V4 Pro 0813 is the escalation tier for knowledge-heavy reasoning, where a wrong answer costs more than the tokens. DeepSeek V4 Flash 0731 is the older text-only option, worth keeping only if your own evaluation still matches its behavior, because V4.1 Flash is now both cheaper and stronger on the tasks most teams run.
Test the models on your own prompts before you route production traffic, and check the current model pages for pricing and IDs.
FAQ
Which DeepSeek V4 model should I use on Novita AI?
Use DeepSeek V4.1 Flash for coding agents, tool use, and image input; DeepSeek V4 Pro 0813 for knowledge-heavy reasoning with a high failure cost; and DeepSeek V4 Flash 0731 only when a text-only workload already matches its behavior.
How much does each DeepSeek V4 model cost on Novita AI?
Checked October 13, 2026: V4 Pro 0813 lists $1.32 input and $3.96 output per 1M tokens, V4 Flash 0731 lists $0.44 and $1.32, and V4.1 Flash lists $0.30 and $1.20.
Is DeepSeek V4.1 Flash cheaper than DeepSeek V4 Flash 0731?
Yes. On Novita AI, V4.1 Flash lists $0.30 per 1M input and $1.20 per 1M output, below V4 Flash 0731’s $0.44 and $1.32, and its cache-read price is lower as well.
Do all three models share the same context window?
Yes. Novita AI lists a 1,048,576-token context window and a 393,216-token maximum output for all three, so context length does not separate them.
Which model supports image input?
Only DeepSeek V4.1 Flash. It accepts text and image input and returns text; V4 Pro 0813 and V4 Flash 0731 are text-only.
Do all three use the same API endpoint?
Yes. They are serverless on Novita AI and use the same OpenAI-compatible chat completions endpoint, so you switch models by changing the model value only.
Sources
- DeepSeek V4 Pro 0813 model page
- DeepSeek V4 Flash 0731 model page
- DeepSeek V4.1 Flash model page
- Novita AI pricing
- DeepSeek-V4.1-Flash model card
