Llama 3.3 70B Instruct vs Qwen3 VL Plus

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokens$0.10Openrouter · Sep 23, 2026Not reported
Output priceFrom · USD / 1M tokens$0.32Openrouter · Sep 23, 2026Not reported
Context windowMaximum documented tokens131K262K
Model facts checkedAug 28, 2026View model evidence →Sep 3, 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

FieldLlama-3.3-70B-InstructQwen3 VL Plus
DeveloperMetaQwen
FamilyLlama 3 3 70b InstructQwen3 VL
ModelLlama-3.3-70B-InstructQwen3 VL Plus
VersionLlama-3.3-70B-InstructQwen3 VL Plus
Lifecycleactiveactive
Released2024-12-062025-12-19
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Video
Output modalitiesTextText
Context window131K262K
Total parameters70.6BUnknown
Active parametersUnknownUnknown
Licensellama3.3Unknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessHugging Face (Standard), Openrouter (Standard), Together Ai (Standard)Alibaba Cloud Model Studio (Standard)
Capabilitieschat, generation, toolschat, generation, reasoning, structured_outputs, tools, vision

Llama 3.3 70B Instruct Capabilities

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

Qwen3 VL Plus Capabilities

chatgenerationreasoningstructured outputstoolsvision
Serving providers1
Canonical IDqwen/qwen3-vl-plus

Primary Evidence

Sources and Freshness

Questions

Llama 3.3 70B Instruct vs Qwen3 VL Plus FAQs

Is Llama 3.3 70B Instruct or Qwen3 VL Plus better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.3 70B Instruct and Qwen3 VL Plus, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Llama 3.3 70B Instruct or Qwen3 VL Plus?+

Llama 3.3 70B Instruct is $0.10 and Qwen3 VL Plus is $1.00 per million tokens, so Llama 3.3 70B Instruct is cheaper on this metric. Llama 3.3 70B Instruct is $0.32 and Qwen3 VL Plus is $10.00 per million tokens, so Llama 3.3 70B Instruct is cheaper on this metric.

Which has a larger context window, Llama 3.3 70B Instruct or Qwen3 VL Plus?+

Qwen3 VL Plus has the larger sourced context window. Llama 3.3 70B Instruct supports 131K and Qwen3 VL Plus supports 262K.

Which performs better in benchmarks, Llama 3.3 70B Instruct or Qwen3 VL Plus?+

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

Can Llama 3.3 70B Instruct or Qwen3 VL Plus be self-hosted?+

Llama 3.3 70B Instruct is the only model in this pair currently marked as self-hostable. Llama 3.3 70B Instruct is open weight; Qwen3 VL Plus is not marked open weight.

Can Llama 3.3 70B Instruct and Qwen3 VL Plus understand images?+

Llama 3.3 70B Instruct is not documented with image input; Qwen3 VL Plus is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Llama 3.3 70B Instruct or Qwen3 VL Plus?+

Neither has a larger sourced maximum output. Llama 3.3 70B Instruct is — and Qwen3 VL Plus is —.

Do Llama 3.3 70B Instruct and Qwen3 VL Plus support reasoning and tool use?+

Llama 3.3 70B Instruct: tool calling. Qwen3 VL Plus: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Llama 3.3 70B Instruct or Qwen3 VL Plus?+

Llama 3.3 70B Instruct has 3 sourced provider routes; Qwen3 VL Plus has 1, so Llama 3.3 70B Instruct has broader tracked availability.

Which offers better value, Llama 3.3 70B Instruct or Qwen3 VL Plus?+

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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