DeepSeek · Mid-tier · 128K context window

DeepSeek R1 pricing for code review

$0.007130 per call at 5,000 input / 2,000 output tokens.

Per call

$0.007130

10K calls/mo

$71.3

Cache savings

75% off input

Batch savings

0% off all

Calculate your DeepSeek R1 costs

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

Configure your usage

5,000
100100K
2,000
5050K
10,000
1001M

Estimated cost

Monthly cost
$71
10,000 calls/month
Cost per call$0.007130
Daily cost$2
Input rate$0.55/MTok
Output rate$2.19/MTok
Analyze your real spend

Quick start

Call DeepSeek R1 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-r1",
    max_tokens=2000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.007130 per call at standard rates
# Input:  $0.55/MTok
# Output: $2.19/MTok

How DeepSeek R1 compares on cost

Per-call cost for all models scoring 50+ on code review benchmarks. Hover for details.

Highest-quality affordable option: Claude Sonnet 5 at $0.0300/call (4.2x the cost, 96/100 quality). DeepSeek R1 is already the cheapest choice for code review.

What drives code review cost

Review is input-heavy in a way generation is not: the diff or file goes in whole, and structured feedback comes back short. That flips the usual optimization: input rate and cache discounts matter more than output rate. Reviewing the same repository repeatedly means the surrounding context is identical call over call, which is exactly the shape prompt caching is designed for.

For DeepSeek R1 specifically, that means output tokens cost 4.0x more than input, at $2.19 vs $0.55 per MTok. At this use case’s 5,000/2,000 token split, output accounts for 61% of the $0.007130 per-call cost.

Complete DeepSeek R1 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$0.555,000
Output$2.192,000

Prompt caching: 75% off input tokens

Caching drops input cost from $0.55 to $0.14/MTok. For repeated system prompts, that saves $0.002049 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$0.007130$71.3$50.81$20.49
50,000 calls$0.007130$356.5$254.06$102.44
100,000 calls$0.007130$713$508.13$204.88
500,000 calls$0.007130$3,565$2,540.63$1,024.38
1,000,000 calls$0.007130$7,130$5,081.25$2,048.75

DeepSeek R1 quality benchmarks for code review

Benchmark data for code review is pending for DeepSeek R1. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for DeepSeek R1. We recommend testing against your own evaluation criteria.

Alternative models for code review

6 models score 80+ on code review benchmarks, sorted by input rate. Cheapest: Claude Sonnet 5 (321% more, 96/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs DeepSeek
Claude Sonnet 5Claude$2.00$10.0096/100$0.0300321% more
Claude Sonnet 4.6Claude$3.00$15.0095/100$0.0450531% more
GPT 5.6 SolGPT$4.00$20.0092/100$0.0600742% more
Claude Opus 4.8Claude$5.00$25.0094/100$0.0750952% more
GPT 5.5GPT$5.00$30.0090/100$0.08501092% more
Claude Fable 5Claude$10.00$50.0095/100$0.15002004% more

About DeepSeek R1

Provider

DeepSeek

Tier

Mid-tier

Context

128K tokens

Released

Jan 2025

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: $0.14/MTok input. No batch discount published. Reasoning model: output includes chain-of-thought tokens. Not yet benchmarked, so never recommended.

Other models from DeepSeek

ModelTierInput $/MTokOutput $/MTokContext
DeepSeek V3Mid-tier$0.27$1.10164K
DeepSeek FlashFast / Budget$0.15$0.601M
DeepSeek V4 ProFlagship$0.66$1.981M

You can compare DeepSeek R1 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 R1 cost for code review per API call?

A typical code review call using DeepSeek R1 costs about $0.007130 per call. This estimate uses 5,000 input tokens and 2,000 output tokens at standard rates. Standard rates are $0.55 per million input tokens and $2.19 per million output tokens.

Is DeepSeek R1 the best model for code review?

Our benchmark data does not yet include a code review ranking for DeepSeek R1. We recommend testing it against your own evaluation criteria before production usage.

What is the cheapest model for code review with good quality?

The most affordable model for code review above 80/100 quality is Claude Sonnet 5. It comes from Claude at $2.00 per million input tokens. Output costs $10.00 per million tokens with a quality score of 96/100. Claude Sonnet 5 costs more per call than DeepSeek R1 but scores higher on quality benchmarks for this task type.

How can I reduce my DeepSeek R1 costs for code review?

Three strategies lower DeepSeek R1 costs for this task type effectively. Prompt caching gives a 75% 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 $0.007130 to about $0.001818 per call.

How does DeepSeek R1 pricing compare to other DeepSeek models?

DeepSeek has 3 other models alongside DeepSeek R1 today: DeepSeek V3 at $0.27/$1.10 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 code review workload prioritizes quality, cost, or speed.

What context window does DeepSeek R1 support?

DeepSeek R1 supports a context window of 128K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For code review, typical calls use 5,000 input and 2,000 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

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