Qwen3 Reranker 8B vs Llama 3.1 70B Instruct

At a Glance

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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 tokens33K131K
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 →

Different Model RolesThese models do not share a sourced market category. Their primary-source facts remain comparable below, while performance claims require matched evidence.

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

FieldQwen3 Reranker 8BLlama-3.1-70B-Instruct
DeveloperQwenMeta
FamilyQwen3 RerankerLlama 3 1 70b Instruct
ModelQwen3 Reranker 8BLlama-3.1-70B-Instruct
VersionQwen3 Reranker 8BLlama-3.1-70B-Instruct
Lifecycleactiveactive
Released2025-05-292024-07-23
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesUnknownText
Context window33K131K
Total parameters8B70.6B
Active parametersUnknownUnknown
Licenseapache-2.0llama3.1
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessFireworks Ai (Standard)Openrouter (Standard)
Capabilitiesmultilingual, reranking, retrievalchat, generation, tools

Qwen3 Reranker 8B Capabilities

multilingualrerankingretrieval
Serving providers1
Canonical IDQwen/Qwen3-Reranker-8B

Llama 3.1 70B Instruct Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Qwen3 Reranker 8B vs Llama 3.1 70B Instruct FAQs

Is Qwen3 Reranker 8B or Llama 3.1 70B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3 Reranker 8B 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, Qwen3 Reranker 8B 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, Qwen3 Reranker 8B or Llama 3.1 70B Instruct?+

Llama 3.1 70B Instruct has the larger sourced context window. Qwen3 Reranker 8B supports 33K and Llama 3.1 70B Instruct supports 131K.

Which performs better in benchmarks, Qwen3 Reranker 8B 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 Qwen3 Reranker 8B or Llama 3.1 70B Instruct be self-hosted?+

Both models have the same recorded self-hosting status: supported. Qwen3 Reranker 8B is open weight; Llama 3.1 70B Instruct is open weight.

Can Qwen3 Reranker 8B and Llama 3.1 70B Instruct understand images?+

Qwen3 Reranker 8B is not 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, Qwen3 Reranker 8B or Llama 3.1 70B Instruct?+

Neither has a larger sourced maximum output. Qwen3 Reranker 8B is — and Llama 3.1 70B Instruct is —.

Do Qwen3 Reranker 8B and Llama 3.1 70B Instruct support reasoning and tool use?+

Qwen3 Reranker 8B: none of these features are definitively sourced. Llama 3.1 70B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3 Reranker 8B or Llama 3.1 70B Instruct?+

Qwen3 Reranker 8B has 1 sourced provider route; Llama 3.1 70B Instruct has 1, a tie.

Which offers better value, Qwen3 Reranker 8B 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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