01 / decision

Decision snapshot

Each figure sits next to the middle of the field, so it can be read as dear or cheap, wide or narrow, rather than floating on its own. Compared against the 370 models tracked here, not against an absolute standard.

Capability

42.0/100

#27 of 35 with published scores

Input / 1M tokens

$0.29

field median $0.40

Output / 1M tokens

$1.14

field median $1.68

Context

164K

field median 262K

Read the coverage before the score. That figure rests on 20% of the weighting: the rest of the categories have no published evidence for this model, and are not counted rather than counted as zero.

02 / overview

What DeepSeek V3 0324 is, and when to reach for it

Four questions, answered separately, because somebody arrives at one of them rather than at the top of the page.

This model has no written explanation yet.

The page is created the moment a model appears in a provider's catalogue, and the writing follows. Until then the measured sections below are the whole page.

What counts as evidence

Follows DeepSeek V3. Superseded by DeepSeek V3.1. See the whole line.

03 / evidence

How much of this is verified

Split by category, so a strong number never hides a thin evidence base. Verified means it was read on the benchmark's own published results; a provider's claim about its own model is shown and labelled rather than dropped.

Published rows

of 19 benchmarks tracked

Independently verified

1 from the provider

Weighting covered

20%

the rest is not measured, not zero

Agentic

0/3

Not measured

Coding

1/3

Provider claim

Reasoning

0/3

Not measured

Multimodal

0/3

Not measured

Knowledge

0/2

Not measured

Multilingual

0/2

Not measured

Instruction following

0/1

Not measured

Maths

0/2

Not measured

04 / ledger

Benchmark ledger

Every published row, grouped by category, each compared with the best published score on the same benchmark. 'Is 64% good' is a question nobody can answer; '26 points behind the leader' is one anybody can.

Coding1 row

Benchmark	Score	Best published	Weight	Evidence
SWE-bench VerifiedReal GitHub issues, resolved and tested.	42%	Gemini 3 Flash Preview75.8% · 33.8 behind	40%	Provider claim

05 / capability

Capability shape

Where this model is strong, and against how many peers. Ranks are against models with evidence in that category, not against every tracked model: ranking against models nobody tested would rank who published, not who is better.

Category recordWriteWorks
Category	Score	Rank	Weight	Benchmarks	Evidence
Agentic	Not measured	Not ranked	22%	0 of 3	Not measured
Coding	42.0	#27 of 3524th percentile	20%	1 of 3	Provider claim
Reasoning	Not measured	Not ranked	17%	0 of 3	Not measured
Multimodal	Not measured	Not ranked	12%	0 of 3	Not measured
Knowledge	Not measured	Not ranked	12%	0 of 2	Not measured
Multilingual	Not measured	Not ranked	7%	0 of 2	Not measured
Instruction following	Not measured	Not ranked	5%	0 of 1	Not measured
Maths	Not measured	Not ranked	5%	0 of 2	Not measured

Category weights are WriteWorks' own and they are a judgement: weighted for what a team buys a model to do. Agentic and coding lead because that is where the work is. Published here rather than hidden, and set out in full on the methodology page.

06 / cost

What it costs

List API rates as last read, each with the date it was confirmed, plus every change recorded since tracking began.

DeepSeek V3 0324 API pricingWriteWorks
Charge	Price	Unit	Read on
Input	$0.29	per 1M tokens	2026-10-05
Output	$1.14	per 1M tokens	2026-10-05

What a month costsWriteWorks
Workload	Input / month	Output / month	Cost
A small product team	20M tokens	5M tokens	$11.50
A busy support assistant	200M tokens	40M tokens	$103.60
A document pipeline	1000M tokens	100M tokens	$404.00

List API rates, no caching and no batch discount, which both providers offer and which change the answer a great deal. Treat these as the ceiling, not the bill.

Price history (4 earlier readings)

2026-10-04: Input $0.25 per 1M tokens
2026-10-04: Output $1.00 per 1M tokens
2026-09-30: Input $0.29 per 1M tokens
2026-09-30: Output $1.14 per 1M tokens

Every reading taken, kept whether it changed or not. This is the part nobody can copy in a week.

07 / specs

Specifications

As listed by the provider's own catalogue and re-read every few hours. Anything absent is absent there too.

SpecificationWriteWorks
Context window	163,840 tokens
Maximum output	115,200 tokens
Modalities	text
Released	24/03/2025
Status	Current

08 / lineage

Lineage

What this model replaced, what replaced it, and what else its provider has in the field.

Also from DeepSeek

All 17 DeepSeek models

09 / line

The line

Every model in this family in release order, so a page from eight months ago says in one glance that two newer ones exist.

Came before

← DeepSeek V3

Came after

DeepSeek V3.1→

01DeepSeek V326/12/2024
02DeepSeek V3 032424/03/2025
03DeepSeek V3.121/08/2025
04DeepSeek V3.1 Terminus22/09/2025
05DeepSeek V3.2 Exp29/09/2025
06DeepSeek V3.201/12/2025

Ordered by release date and worked out from the naming, so a new member slots in as soon as its page exists. A retired model keeps its page and its place in the line.

10 / notes

WriteWorks notes

What this model changes for a brand trying to be cited in AI answers, and every change logged since it launched.

Change log

Every release, price and feature change for DeepSeek V3 0324, newest first. They also appear on the DeepSeek page.

5 Oct 2026
DeepSeek V3 0324 pricing changed
Model: DeepSeek V3 0324 Input was $0.25 per 1M tokens, now $0.29 per 1M tokens Output was $1 per 1M tokens, now $1.14 per 1M tokens
Pricing
4 Oct 2026
DeepSeek V3 0324 pricing changed
Model: DeepSeek V3 0324 Input was $0.29 per 1M tokens, now $0.25 per 1M tokens Output was $1.14 per 1M tokens, now $1 per 1M tokens
Pricing

11 / questions

Questions

The things people ask about this model, answered from what is on this page rather than from anywhere else.

What does DeepSeek V3 0324 cost?: $0.29 per million input tokens and $1.14 per million output tokens, as last read from the provider. The cost section works that into a monthly figure.
How current is this page?: The catalogue behind it is re-read every three hours, and the stamp at the top says when it last confirmed. A re-check that finds nothing changed updates that stamp and deliberately does not touch the page’s modified date.
Why are some sections empty?: Because nothing has been published that can be linked to. An empty section is better than a number you cannot check. The methodology sets out what counts.

WriteWorks

Is DeepSeek V3 0324 recommending you?

Models change what gets cited. WriteWorks tracks whether 10+ AI platforms, from ChatGPT and Claude to Gemini and Perplexity, name your brand or your competitors, and shows you the content gaps to close.

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