DeepSeek V4 Flash Base vs Llama 3.3 70B Instruct

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.10Openrouter · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$0.32Openrouter · Sep 22, 2026
Context windowMaximum documented tokens1,049K131K
Model facts checkedAug 28, 2026View model evidence →Aug 28, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldDeepSeek-V4-Flash-BaseLlama-3.3-70B-Instruct
DeveloperDeepSeekMeta
FamilyDeepseek V4 Flash BaseLlama 3 3 70b Instruct
ModelDeepSeek-V4-Flash-BaseLlama-3.3-70B-Instruct
VersionDeepSeek-V4-Flash-BaseLlama-3.3-70B-Instruct
Lifecycleactiveactive
Released2026-04-242024-12-06
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window1,049K131K
Total parameters292B70.6B
Active parametersUnknownUnknown
LicenseUnknownllama3.3
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownHugging Face (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitiesgenerationchat, generation, tools

DeepSeek V4 Flash Base Capabilities

generation
Serving providers0
Canonical IDdeepseek-ai/DeepSeek-V4-Flash-Base

Llama 3.3 70B Instruct Capabilities

chatgenerationtools
Serving providers3
Canonical IDmeta-llama/Llama-3.3-70B-Instruct

Primary Evidence

Sources and Freshness

Questions

DeepSeek V4 Flash Base vs Llama 3.3 70B Instruct FAQs

Is DeepSeek V4 Flash Base or Llama 3.3 70B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4 Flash Base and Llama 3.3 70B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, DeepSeek V4 Flash Base or Llama 3.3 70B Instruct?+

Only Llama 3.3 70B Instruct has a directly sourced input price: $0.10 per million tokens. Only Llama 3.3 70B Instruct has a directly sourced output price: $0.32 per million tokens.

Which has a larger context window, DeepSeek V4 Flash Base or Llama 3.3 70B Instruct?+

DeepSeek V4 Flash Base has the larger sourced context window. DeepSeek V4 Flash Base supports 1,049K and Llama 3.3 70B Instruct supports 131K.

Which performs better in benchmarks, DeepSeek V4 Flash Base or Llama 3.3 70B Instruct?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can DeepSeek V4 Flash Base or Llama 3.3 70B Instruct be self-hosted?+

Both models have the same recorded self-hosting status: supported. DeepSeek V4 Flash Base is open weight; Llama 3.3 70B Instruct is open weight.

Can DeepSeek V4 Flash Base and Llama 3.3 70B Instruct understand images?+

DeepSeek V4 Flash Base is not documented with image input; Llama 3.3 70B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, DeepSeek V4 Flash Base or Llama 3.3 70B Instruct?+

Neither has a larger sourced maximum output. DeepSeek V4 Flash Base is — and Llama 3.3 70B Instruct is —.

Do DeepSeek V4 Flash Base and Llama 3.3 70B Instruct support reasoning and tool use?+

DeepSeek V4 Flash Base: none of these features are definitively sourced. Llama 3.3 70B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, DeepSeek V4 Flash Base or Llama 3.3 70B Instruct?+

DeepSeek V4 Flash Base has 0 sourced provider routes; Llama 3.3 70B Instruct has 3, so Llama 3.3 70B Instruct has broader tracked availability.

Which offers better value, DeepSeek V4 Flash Base or Llama 3.3 70B Instruct?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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