DeepSeek vs Meta Llama Pricing
Meta Llama is cheaper than DeepSeek at the entry level: Llama 3.2 3B Instruct costs $0.020 per 1M output tokens against $0.100 for DeepSeek R1 0528 Qwen3 8B — 5.0× the price. On current flagships, DeepSeek's DeepSeek R1 costs $2.19/1M output against $4.00/1M for Meta Llama's Llama 3.1 405B (base). Prices are USD, current as of August 11, 2026.
Per-million-token pricing for DeepSeek and Meta Llama, with side-by-side flagship models, cheapest tiers, and context windows. Pricing data syncs weekly from a continuously-updated model catalog — last updated August 11, 2026.
Who wins on what
Cheapest input tokens
$0.02/1MDeepSeek
DeepSeek R1 0528 Qwen3 8B — $0.02/1M input
Cheapest output tokens
$0.02/1MMeta Llama
Llama 3.2 3B Instruct — $0.02/1M output
Longest context window
1.0MMeta Llama
Llama 4 Maverick — 1.0M input tokens
Lowest average output cost
$0.67/1MMeta Llama
Provider-wide average across 22 models
Largest model catalog
22 modelsMeta Llama
More options to match cost vs capability
Most reasoning models
3 modelsDeepSeek
Models with dedicated reasoning / thinking support
Open-weights available
YesDeepSeek
Offers open-weight models you can self-host
Side-by-side
DeepSeek
Full DeepSeek pricing →Cheapest input
$0.020
DeepSeek R1 0528 Qwen3 8B
Cheapest output
$0.100
DeepSeek R1 0528 Qwen3 8B
Longest context
1.0M
DeepSeek Chat
Avg output / 1M
$0.790
Across catalog
Cheapest cached input
$0.0028
DeepSeek Chat
| Model | In/1M | Out/1M | Ctx |
|---|---|---|---|
| DeepSeek V4 Flash ReasoningToolsCache | $0.140 | $0.280 | 1.0M |
| DeepSeek V4 Pro ReasoningToolsCache | $0.435 | $0.870 | 1.0M |
| DeepSeek Chat ToolsCache | $0.140 | $0.280 | 1.0M |
| DeepSeek Reasoner ReasoningToolsCache | $0.140 | $0.280 | 1.0M |
| DeepSeek R1 | $0.550 | $2.19 | 66K |
| DeepSeek R1 0528 Qwen3 8B | $0.020 | $0.100 | 33K |
Meta Llama
Full Meta Llama pricing →Cheapest input
$0.020
Llama 3.1 8B Instruct
Cheapest output
$0.020
Llama 3.2 3B Instruct
Longest context
1.0M
Llama 4 Maverick
Avg output / 1M
$0.674
Across catalog
| Model | In/1M | Out/1M | Ctx |
|---|---|---|---|
| Llama 3.1 405B (base) | $4.00 | $4.00 | 33K |
| Llama 3.1 405B Instruct | $3.50 | $3.50 | 131K |
| Llama 4 Maverick | $0.150 | $0.600 | 1.0M |
| Llama 3 70B Instruct | $0.300 | $0.400 | 8K |
| Llama 3.1 70B Instruct | $0.400 | $0.400 | 131K |
| Llama 3.2 3B Instruct | $0.020 | $0.020 | 131K |
All prices in USD per 1 million tokens. Showing top 6 models per provider, sorted by output cost.
Frequently asked questions
Is DeepSeek or Meta Llama cheaper?
Meta Llama has the cheaper entry point at $0.02/1M output (Llama 3.2 3B Instruct — $0.02/1M output). Provider-wide, DeepSeek averages $0.790/1M output against $0.674/1M for Meta Llama. Which is cheaper for you depends on which model tier your workload actually needs.
How much do DeepSeek and Meta Llama cost per 1M tokens?
DeepSeek starts at $0.100 per 1M output tokens (DeepSeek R1 0528 Qwen3 8B), with its current flagship DeepSeek R1 at $2.19. Meta Llama starts at $0.020 (Llama 3.2 3B Instruct), with Llama 3.1 405B (base) at $4.00. Input tokens cost less than output on both.
Which has the larger context window, DeepSeek or Meta Llama?
Meta Llama — Llama 4 Maverick — 1.0M input tokens. For comparison, DeepSeek's largest is 1.0M tokens (DeepSeek Chat) and Meta Llama's is 1.0M tokens (Llama 4 Maverick).
Which has more reasoning models, DeepSeek or Meta Llama?
DeepSeek lists 3 reasoning models and Meta Llama lists 0. Reasoning models bill their internal thinking as output tokens, so a reasoning call costs several times a standard completion of the same visible length — compare them on total tokens billed, not headline rate.
Can I self-host DeepSeek or Meta Llama models?
DeepSeek publishes open-weight models you can run on your own hardware; Meta Llama does not. Self-hosting swaps per-token pricing for GPU-hour cost, which usually only wins above sustained high utilisation — below that, hosted inference is cheaper.
Should I switch from DeepSeek to Meta Llama to save money?
Only if the cheaper model still meets your quality bar. Token price is one input; the ones that decide your bill are prompt size, response length, retries and how much conversation history you resend each turn. Model the switch against your real traffic before committing. Prices here are current as of August 11, 2026.
Related comparisons
Run the numbers for your workload
Calcaas multiplies per-token costs by your real usage patterns — inputs, outputs, retries, and conversation history — across both providers in one model.