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HomeModelsDeepSeek V3
DeepSeekBudget

DeepSeek V3

GPT-4o-class coding quality at under $0.30/1M — the best value in the directory.

87
Coding
74
Writing
80
Research
10
Images
96
Value
62
Long Context
Published benchmarks
42%
SWE-bench
1,305
Arena Elo
88.5%
MMLU
59.1%
GPQA
90.2%
MATH
Use this when

Coding, reasoning, and general tasks at extreme cost efficiency

Skip this if

Your team has data sovereignty requirements or needs enterprise-grade reliability guarantees.

Pricing
$0.27/1M in
$1.10/1M out
→0%since Jun 2026
Context
128k tokens
Speed
Fast

DeepSeek V3 shocked the market on release. At this price point with this capability level, it forces a reconsideration of when premium models are actually worth it.

How to access
API
$0.27/1M input tokens
Subscription = chat interface. API = build with it. Compare all subscription plans
Switch to instead if...
Best overall
GPT-6 Astra
Cheaper option
GPT-5.1-Codex-Max
Faster option
Claude 3.5 Sonnet

Strengths

GPT-4o class coding and reasoning at under $0.30/1M input tokens

Open-source weights available for self-hosting

Strong performance on HumanEval and coding benchmarks relative to price

Weaknesses

Chinese-origin model raises data sovereignty concerns for some enterprise teams

Slightly weaker on nuanced English writing tone compared to Claude and GPT

Less reliable for complex multi-step agentic workflows vs frontier models

Real-world use cases

What people actually use DeepSeek V3 for.

High-volume code generation and review pipelines where GPT-4o-class quality is needed at budget pricing

Research synthesis and document analysis at scale without premium model costs

General-purpose assistant workflows where open-source is preferred over proprietary models

How DeepSeek V3 compares

The nearest models people weigh against it, and what actually separates them.

vs Claude 3.5 Sonnet — Against Claude 3.5 Sonnet (Anthropic), DeepSeek V3 runs about 96% cheaper per token, gives up 1.6x on context and answers faster. Take DeepSeek V3 unless you specifically need what Claude 3.5 Sonnet does better.

vs Claude Fable 5 — Against Claude Fable 5 (Anthropic), DeepSeek V3 runs about 98% cheaper per token, gives up 7.8x on context and answers faster. Take DeepSeek V3 unless you specifically need what Claude Fable 5 does better.

vs Claude Fable 5.1 — Against Claude Fable 5.1 (Anthropic), DeepSeek V3 runs about 98% cheaper per token, gives up 7.8x on context and answers faster. Take DeepSeek V3 unless you specifically need what Claude Fable 5.1 does better.

Price History

DeepSeek V3 pricing over time

→0% since Jun 12

$0.292$0.281$0.270$0.259$0.248Jun 12Jul 4Jul 22Aug 8Sep 2Sep 20

90 data points · tracked daily since Jun 12, 2026

Ready to try it?

Start using DeepSeek V3

Coding, reasoning, and general tasks at extreme cost efficiency. Start free — no card required.

Try DeepSeek V3 freeCompare alternatives

Recommendations are made independently based on real-world use and public benchmarks. See our disclosures for details.

Compare alternatives

Similar models worth checking before you commit.

All DeepSeek V3 alternatives →
AnthropicPremium

Claude 3.5 Sonnet

Claude 3.5 Sonnet is Anthropic's mid-cycle flagship model, balancing strong reasoning, coding, and instruction-following with a 200K context window. It sits between Haiku and Opus in Anthropic's lineup, offering near-flagship quality at a lower cost than top-tier models.

Verdict
One of the best models for coding and complex instruction-following, but its premium pricing demands premium use cases.
Quality score
81%
Pricing
$6.00/1M in
$30.00/1M out
Speed
Balanced
3/5 speed
Context
200k tokens
Pricing at $6 input / $30 output per million tokens is significantly higher than GPT-4o ($2.50/$10). Best accessed via Anthropic API or Amazon Bedrock. Claude 3.5 Sonnet (October 2024 version) supersedes the June 2024 release with improved performance.
CodingLong ContextInstruction FollowingReasoningPremium
Best for
Complex coding tasks, multi-step reasoning, and long-document analysis where GPT-4o-class quality is needed without paying for the absolute top tier.
View model
AnthropicPremium

Claude Fable 5

Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.

Verdict
New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses.
Coding leaderSWE-Bench Pro #1Mythos-classParallel subagentsAgenticLong contextPremiumNew
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
View model
AnthropicPremium

Claude Fable 5.1

Anthropic's September 1, 2026 frontier release and the new capability ceiling for coding, agents, and scientific work. Base pricing is unchanged at $10/$50, but cache reads dropped 75% to $0.25/1M — roughly 25% cheaper on typical workloads and up to 45% cheaper on agentic ones. 1M context, 128K output, adaptive thinking always on.

Verdict
New frontier leader — better than Fable 5 on every published benchmark, and cheaper to run.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Released September 1, 2026 alongside Claude Mythos 5.1, the first update to the Mythos-class line since Fable 5 on June 9. API ID claude-fable-5-1; generally available on the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry. Published launch numbers (Fable 5.1 / Fable 5 / Opus 5 / GPT-5.6 Sol): Terminal-Bench-Science 0.1 52.6 / 24.7 / 29.0 / 22.4; Terminal-Bench 4.0 55.8 / 42.0 / 52.3 / 37.3; CursorBench 3.2.0 73.4 / 70.5 / 70.0 / 67.2; AutomationBench 31.4 / 17.1 / 26.9 / 19.6; OSWorld 2.0 strict 41.7 / 36.1 / 39.6; Humanity's Last Exam (no tools) 60.9 / 57.8 / 56.6; GDPval-AA v2 1853 / 1723 / 1824 / 1711. GDPval-AA v2 is rescaled from the v1 numbers quoted on the Fable 5 page and is not directly comparable to them.
Coding leaderFrontierAgenticMythos-classLong contextCheaper cachingPremiumNew
Best for
Frontier agentic coding, long-horizon autonomous work, and agentic scientific research
View model

DeepSeek V3 head-to-head

All DeepSeek V3 alternatives →DeepSeek vs Claude →DeepSeek vs Gemini →GPT-4o vs DeepSeek V3 →DeepSeek V3 vs Claude Sonnet 4.6 →DeepSeek V3 vs GPT-5.4 →DeepSeek V3 vs Gemini 3.1 Pro →DeepSeek R1 vs DeepSeek V3 →DeepSeek V3 vs Gemini 3.1 Flash →DeepSeek V3 vs Claude Opus 4.6 →DeepSeek V3 vs Llama 4 Maverick →DeepSeek V3 vs Mistral Large 2 →DeepSeek V3 vs Codestral 25.01 →Grok 4 vs DeepSeek V3 →Claude Opus 4.7 vs DeepSeek V3 →GPT-5.5 vs DeepSeek V3 →GPT-5.2 vs DeepSeek V3 →Claude 4 Haiku vs DeepSeek V3 →GPT-5.2 Mini vs DeepSeek V3 →View benchmark scores →

FAQ

How much does DeepSeek V3 cost?

DeepSeek V3 costs $0.27 per million input tokens and $1.1 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $4.90 at list price, before any batch or caching discounts.

What is DeepSeek V3 best for?

DeepSeek V3 is best for coding, reasoning, and general tasks at extreme cost efficiency. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and fast speed.

When should I avoid DeepSeek V3?

Your team has data sovereignty requirements or needs enterprise-grade reliability guarantees.

What is a cheaper alternative to DeepSeek V3?

GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against DeepSeek V3's $0.27/1M/1M. The strongest choice for serious software engineering work, provided you can absorb the output-side pricing. Compare it first if DeepSeek V3's pricing is the thing stopping you.

What is a faster alternative to DeepSeek V3?

Claude 3.5 Sonnet — balanced against DeepSeek V3's fast, with 200k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.

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