Seed 2.1 Turbo vs Llama 3.1 70B Instruct

At a Glance

Compare
Seed 2.1 TurboByteDance Seed
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.40Openrouter · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$0.40Openrouter · Sep 22, 2026
Context windowMaximum documented tokensNot reported131K
Model facts checkedSep 3, 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

FieldSeed 2.1 TurboLlama-3.1-70B-Instruct
DeveloperByteDance SeedMeta
FamilySeed 2 1Llama 3 1 70b Instruct
ModelSeed 2.1 TurboLlama-3.1-70B-Instruct
VersionSeed 2.1 TurboLlama-3.1-70B-Instruct
Lifecycleactiveactive
Released2026-06-232024-07-23
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, VideoText
Output modalitiesTextText
Context windowUnknown131K
Total parametersUnknown70.6B
Active parametersUnknownUnknown
LicenseUnknownllama3.1
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessUnknownOpenrouter (Standard)
Capabilitiesagents, chat, generation, reasoning, structured_outputs, toolschat, generation, tools

Seed 2.1 Turbo Capabilities

agentschatgenerationreasoningstructured outputstools
Serving providers0
Canonical IDbytedance-seed/seed-2.1-turbo

Llama 3.1 70B Instruct Capabilities

chatgenerationtools
Serving providers1
Canonical IDmeta-llama/Llama-3.1-70B-Instruct

Primary Evidence

Sources and Freshness

Questions

Seed 2.1 Turbo vs Llama 3.1 70B Instruct FAQs

Is Seed 2.1 Turbo or Llama 3.1 70B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Seed 2.1 Turbo and Llama 3.1 70B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Seed 2.1 Turbo or Llama 3.1 70B Instruct?+

Only Llama 3.1 70B Instruct has a directly sourced input price: $0.40 per million tokens. Only Llama 3.1 70B Instruct has a directly sourced output price: $0.40 per million tokens.

Which has a larger context window, Seed 2.1 Turbo or Llama 3.1 70B Instruct?+

Neither model has a larger sourced context window in this comparison. Seed 2.1 Turbo is — and Llama 3.1 70B Instruct is 131K.

Which performs better in benchmarks, Seed 2.1 Turbo or Llama 3.1 70B Instruct?+

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

Can Seed 2.1 Turbo or Llama 3.1 70B Instruct be self-hosted?+

Llama 3.1 70B Instruct is the only model in this pair currently marked as self-hostable. Seed 2.1 Turbo is not marked open weight; Llama 3.1 70B Instruct is open weight.

Can Seed 2.1 Turbo and Llama 3.1 70B Instruct understand images?+

Seed 2.1 Turbo is documented with image input; Llama 3.1 70B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Seed 2.1 Turbo or Llama 3.1 70B Instruct?+

Neither has a larger sourced maximum output. Seed 2.1 Turbo is — and Llama 3.1 70B Instruct is —.

Do Seed 2.1 Turbo and Llama 3.1 70B Instruct support reasoning and tool use?+

Seed 2.1 Turbo: reasoning, tool calling, and image input. Llama 3.1 70B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Seed 2.1 Turbo or Llama 3.1 70B Instruct?+

Seed 2.1 Turbo has 0 sourced provider routes; Llama 3.1 70B Instruct has 1, so Llama 3.1 70B Instruct has broader tracked availability.

Which offers better value, Seed 2.1 Turbo or Llama 3.1 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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