DeepSeek · Flagship · 1M context window
$0.000528 per call at 500 input / 100 output tokens.
Per call
$0.000528
10K calls/mo
$5.28
Cache savings
97% off input
Batch savings
0% off all
Adjust token counts, volume, and discount toggles to model your sentiment analysis spend. Prices verified daily against provider pricing pages.
Call DeepSeek V4 Pro with the OpenAI Python SDK pointed at api.deepseek.com:
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.deepseek.com/v1",
api_key=os.environ["DEEPSEEK_API_KEY"],
)
response = client.chat.completions.create(
model="deepseek-v4-pro",
max_tokens=100,
messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.000528 per call at standard rates
# Input: $0.66/MTok
# Output: $1.98/MTokPer-call cost for all models scoring 50+ on sentiment analysis benchmarks. Hover for details.
Cheapest viable option: GPT 5.6 Luna at $0.000220/call (58% less, 91/100 quality).
Short text in, a label or score out: the cheapest shape an API call can take. Output pricing is irrelevant at this size. Because these run in bulk over historical data as often as in real time, the batch API discount typically applies, and the effective rate lands well below list.
For DeepSeek V4 Pro specifically, that means output tokens cost 3.0x more than input, at $1.98 vs $0.66 per MTok. At this use case’s 500/100 token split, output accounts for 38% of the $0.000528 per-call cost.
| Direction | $/MTok | Tokens per call |
|---|---|---|
| Input | $0.66 | 500 |
| Output | $1.98 | 100 |
Caching drops input cost from $0.66 to $0.02/MTok. For repeated system prompts, that saves $0.000319 per call.
Submit requests asynchronously and receive 0% off all token costs. This works best for offline pipelines where latency requirements are flexible.
| Monthly volume | Cost per call | Standard monthly | Cached monthly | You save with caching |
|---|---|---|---|---|
| 10,000 calls | $0.000528 | $5.28 | $2.09 | $3.19 |
| 50,000 calls | $0.000528 | $26.4 | $10.44 | $15.96 |
| 100,000 calls | $0.000528 | $52.8 | $20.89 | $31.91 |
| 500,000 calls | $0.000528 | $264 | $104.45 | $159.56 |
| 1,000,000 calls | $0.000528 | $528 | $208.89 | $319.11 |
Benchmark data for sentiment analysis is pending for DeepSeek V4 Pro. Test against your own evaluation suite before moving to production.
Benchmark data is not yet available for DeepSeek V4 Pro. We recommend testing against your own evaluation criteria.
12 models score 80+ on sentiment analysis benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (58% less, 91/100 quality).
| Model | Provider | Input $/MTok | Output $/MTok | Quality | Per call | vs DeepSeek |
|---|---|---|---|---|---|---|
| GPT 5.6 Luna | GPT | $0.20 | $1.20 | 91/100 | $0.000220 | 58% cheaper |
| Gemini 3.5 Flash-Lite | Gemini | $0.30 | $2.50 | 85/100 | $0.000400 | 24% cheaper |
| Gemini 3 Flash | Gemini | $0.50 | $3.00 | 88/100 | $0.000550 | 4% more |
| Claude Haiku 4.5 | Claude | $1.00 | $5.00 | 90/100 | $0.001000 | 89% more |
| Gemini 3.5 Flash | Gemini | $1.50 | $9.00 | 92/100 | $0.001650 | 212% more |
| Claude Sonnet 5 | Claude | $2.00 | $10.00 | 86/100 | $0.002000 | 279% more |
| GPT 5.6 Terra | GPT | $2.00 | $12.00 | 89/100 | $0.002200 | 317% more |
| Gemini 3.1 Pro | Gemini | $2.00 | $12.00 | 86/100 | $0.002200 | 317% more |
| GPT 5.4 | GPT | $2.50 | $15.00 | 88/100 | $0.002750 | 421% more |
| Claude Sonnet 4.6 | Claude | $3.00 | $15.00 | 84/100 | $0.003000 | 468% more |
| GPT 5.6 Sol | GPT | $4.00 | $20.00 | 86/100 | $0.004000 | 658% more |
| GPT 5.5 | GPT | $5.00 | $30.00 | 85/100 | $0.005500 | 942% more |
Provider
DeepSeek
Tier
Flagship
Context
1M tokens
Released
Not published
Prices are off-peak rates from api-docs.deepseek.com (read 2026-10-11). Peak-hour prices are 2x the listed input and output rates — Tokeven does not model time-of-day tiers; off-peak is used as the base. Cache hit: $0.022/MTok input. No batch discount published. Not yet benchmarked, so never recommended.
| Model | Tier | Input $/MTok | Output $/MTok | Context |
|---|---|---|---|---|
| DeepSeek V3 | Mid-tier | $0.27 | $1.10 | 164K |
| DeepSeek R1 | Mid-tier | $0.55 | $2.19 | 128K |
| DeepSeek Flash | Fast / Budget | $0.15 | $0.60 | 1M |
You can compare DeepSeek V4 Pro head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.
See how DeepSeek V4 Pro costs change across different workload types.
Code Generation
$0.009240/call
Unit Test Generation
$0.0119/call
SQL Generation
$0.002970/call
API Generation
$0.0139/call
Code Refactoring
$0.0106/call
Code Review
$0.007260/call
PR Review
$0.0112/call
Security Review
$0.008910/call
Bug Detection
$0.007260/call
Document Summarization
$0.008580/call
PDF Summarization
$0.0129/call
Meeting Notes
$0.009240/call
Email Summarization
$0.002970/call
Chatbot
$0.003300/call
RAG Pipeline
$0.006930/call
Customer Support Bot
$0.003960/call
FAQ Bot
$0.002574/call
Data Extraction
$0.004620/call
JSON Extraction
$0.003564/call
Invoice Parsing
$0.002508/call
Resume Parsing
$0.003234/call
Chain of Thought
$0.0119/call
Legal Analysis
$0.0145/call
Math Reasoning
$0.006930/call
Financial Analysis
$0.0132/call
Content Moderation
$0.000528/call
Categorization
$0.000825/call
Intent Detection
$0.000396/call
Copywriting
$0.004290/call
Blog Writing
$0.0165/call
Marketing Copy
$0.006468/call
Product Descriptions
$0.003300/call
A typical sentiment analysis call using DeepSeek V4 Pro costs about $0.000528 per call. This estimate uses 500 input tokens and 100 output tokens at standard rates. Standard rates are $0.66 per million input tokens and $1.98 per million output tokens.
Our benchmark data does not yet include a sentiment analysis ranking for DeepSeek V4 Pro. We recommend testing it against your own evaluation criteria before production usage.
The most affordable model for sentiment analysis above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 91/100. Switching from DeepSeek V4 Pro to GPT 5.6 Luna saves about 58% per API call.
Three strategies lower DeepSeek V4 Pro costs for this task type effectively. Prompt caching gives a 97% discount on input tokens when reusing system prompts. The batch API gives 0% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.000528 to about $0.000017 per call.
DeepSeek has 3 other models alongside DeepSeek V4 Pro today: DeepSeek V3 at $0.27/$1.10 per million tokens (mid-tier), DeepSeek R1 at $0.55/$2.19 per million tokens (mid-tier), DeepSeek Flash at $0.15/$0.60 per million tokens (fast / budget). The right choice depends on whether your sentiment analysis workload prioritizes quality, cost, or speed.
DeepSeek V4 Pro supports a context window of 1M tokens per API call. This sets the maximum combined length of your input prompt and generated response. For sentiment analysis, typical calls use 500 input and 100 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.
This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.