DeepSeek · Mid-tier · 164K context window

DeepSeek V3 pricing for legal analysis

$0.007100 per call at 10,000 input / 4,000 output tokens.

Per call

$0.007100

10K calls/mo

$71

Cache savings

74% off input

Batch savings

0% off all

Calculate your DeepSeek V3 costs

Adjust token counts, volume, and discount toggles to model your legal analysis spend. Prices verified daily against provider pricing pages.

Configure your usage

10,000
100100K
4,000
5050K
10,000
1001M

Estimated cost

Monthly cost
$71
10,000 calls/month
Cost per call$0.007100
Daily cost$2
Input rate$0.27/MTok
Output rate$1.10/MTok
Analyze your real spend

Quick start

Call DeepSeek V3 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-v3",
    max_tokens=4000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.007100 per call at standard rates
# Input:  $0.27/MTok
# Output: $1.10/MTok

What drives legal analysis cost

Legal work is heavy on both sides: long source documents in, detailed analysis out. It is also the case where accuracy is worth the most, so the cheapest-viable-model logic that works for classification does not apply. Long contracts frequently cross long-context pricing thresholds, which can re-rate the entire request rather than just the excess.

For DeepSeek V3 specifically, that means output tokens cost 4.1x more than input, at $1.10 vs $0.27 per MTok. At this use case’s 10,000/4,000 token split, output accounts for 62% of the $0.007100 per-call cost.

Complete DeepSeek V3 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$0.2710,000
Output$1.104,000

Prompt caching: 74% off input tokens

Caching drops input cost from $0.27 to $0.07/MTok. For repeated system prompts, that saves $0.002001 per call.

Batch API: 0% off all tokens

Submit requests asynchronously and receive 0% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.007100$71$50.99$20.01
50,000 calls$0.007100$355$254.97$100.04
100,000 calls$0.007100$710$509.93$200.07
500,000 calls$0.007100$3,550$2,549.65$1,000.35
1,000,000 calls$0.007100$7,100$5,099.3$2,000.7

DeepSeek V3 quality benchmarks for legal analysis

Benchmark data for legal analysis is pending for DeepSeek V3. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for DeepSeek V3. We recommend testing against your own evaluation criteria.

Alternative models for legal analysis

22 models score 80+ on legal analysis benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (4% less, 86/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs DeepSeek
GPT 5.6 LunaGPT$0.20$1.2086/100$0.0068004% cheaper
Gemini 3.6 FlashGemini$0.75$3.7585/100$0.0225217% more
Gemini 3.7 FlashGemini$0.75$3.7588/100$0.0225217% more
Gemini 3.8 FlashGemini$0.75$3.7589/100$0.0225217% more
Claude Sonnet 5Claude$2.00$10.0089/100$0.0600745% more
GPT 5.6 TerraGPT$2.00$12.0091/100$0.0680858% more
GPT 6 SolGPT$2.00$10.0089/100$0.0600745% more
Gemini 3.1 ProGemini$2.00$12.0084/100$0.0680858% more
Grok 4.6Grok$2.00$6.0091/100$0.0440520% more
Grok 4.5Grok$2.00$6.0087/100$0.0440520% more
GPT 5.4GPT$2.50$15.0088/100$0.08501097% more
Claude Sonnet 4.6Claude$3.00$15.0085/100$0.09001168% more
Claude Opus 5.5Claude$4.00$20.0092/100$0.12001590% more
GPT 5.6 SolGPT$4.00$20.0092/100$0.12001590% more
Claude Opus 4.8Claude$5.00$25.0089/100$0.15002013% more
Claude Opus 5Claude$5.00$25.0091/100$0.15002013% more
Claude Opus 4.7Claude$5.00$25.0087/100$0.15002013% more
Claude Opus 4.6Claude$5.00$25.0089/100$0.15002013% more
GPT 5.5GPT$5.00$30.0090/100$0.17002294% more
Claude Fable 5.1Claude$10.00$50.0092/100$0.30004125% more
Claude Fable 5Claude$10.00$50.0090/100$0.30004125% more
GPT 6 AstraGPT$10.00$50.0093/100$0.30004125% more

About DeepSeek V3

Provider

DeepSeek

Tier

Mid-tier

Context

164K tokens

Released

Dec 2024

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: $0.07/MTok input. No batch discount published. Not yet benchmarked, so never recommended.

Other models from DeepSeek

ModelTierInput $/MTokOutput $/MTokContext
DeepSeek R1Mid-tier$0.55$2.19128K
DeepSeek FlashFast / Budget$0.15$0.601M
DeepSeek V4 ProFlagship$0.66$1.981M

You can compare DeepSeek V3 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.

Frequently asked questions

How much does DeepSeek V3 cost for legal analysis per API call?

A typical legal analysis call using DeepSeek V3 costs about $0.007100 per call. This estimate uses 10,000 input tokens and 4,000 output tokens at standard rates. Standard rates are $0.27 per million input tokens and $1.10 per million output tokens.

Is DeepSeek V3 the best model for legal analysis?

Our benchmark data does not yet include a legal analysis ranking for DeepSeek V3. We recommend testing it against your own evaluation criteria before production usage.

What is the cheapest model for legal analysis with good quality?

The most affordable model for legal 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 86/100. Switching from DeepSeek V3 to GPT 5.6 Luna saves about 4% per API call.

How can I reduce my DeepSeek V3 costs for legal analysis?

Three strategies lower DeepSeek V3 costs for this task type effectively. Prompt caching gives a 74% 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 $0.007100 to about $0.001839 per call.

How does DeepSeek V3 pricing compare to other DeepSeek models?

DeepSeek has 3 other models alongside DeepSeek V3 today: DeepSeek R1 at $0.55/$2.19 per million tokens (mid-tier), DeepSeek Flash at $0.15/$0.60 per million tokens (fast / budget), DeepSeek V4 Pro at $0.66/$1.98 per million tokens (flagship). The right choice depends on whether your legal analysis workload prioritizes quality, cost, or speed.

What context window does DeepSeek V3 support?

DeepSeek V3 supports a context window of 164K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For legal analysis, typical calls use 10,000 input and 4,000 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

Track what you spend on AI

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.