Qwen3.5 35B A3B vs Llama 4 Maverick 17B 128E

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokens$0.14Deepinfra · Sep 21, 2026Not reported
Output priceFrom · USD / 1M tokens$1.00Deepinfra · Sep 21, 2026Not reported
Context windowMaximum documented tokens262K1,000K
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

FieldQwen3.5-35B-A3BLlama-4-Maverick-17B-128E
DeveloperQwenMeta
FamilyQwen3 5 35b A3bLlama 4 Maverick 17b 128e
ModelQwen3.5-35B-A3BLlama-4-Maverick-17B-128E
VersionQwen3.5-35B-A3BLlama-4-Maverick-17B-128E
Lifecycleactiveactive
ReleasedUnknown2025-04-05
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image
Output modalitiesTextText
Context window262K1,000K
Total parameters36B401.6B
Active parameters3B17B
Licenseapache-2.0other
Open weightsYesYes
API availableYesUnknown
Self-hostableYesYes
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)Unknown
Capabilitieschat, generation, reasoning, toolschat, generation, tools

Qwen3.5 35B A3B Capabilities

chatgenerationreasoningtools
Serving providers4
Canonical IDQwen/Qwen3.5-35B-A3B

Llama 4 Maverick 17B 128E Capabilities

chatgenerationtools
Serving providers0
Canonical IDmeta-llama/Llama-4-Maverick-17B-128E

Primary Evidence

Sources and Freshness

Questions

Qwen3.5 35B A3B vs Llama 4 Maverick 17B 128E FAQs

Is Qwen3.5 35B A3B or Llama 4 Maverick 17B 128E better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 35B A3B and Llama 4 Maverick 17B 128E, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Qwen3.5 35B A3B or Llama 4 Maverick 17B 128E?+

Only Qwen3.5 35B A3B has a directly sourced input price: $0.14 per million tokens. Only Qwen3.5 35B A3B has a directly sourced output price: $1.00 per million tokens.

Which has a larger context window, Qwen3.5 35B A3B or Llama 4 Maverick 17B 128E?+

Llama 4 Maverick 17B 128E has the larger sourced context window. Qwen3.5 35B A3B supports 262K and Llama 4 Maverick 17B 128E supports 1,000K.

Which performs better in benchmarks, Qwen3.5 35B A3B or Llama 4 Maverick 17B 128E?+

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

Can Qwen3.5 35B A3B or Llama 4 Maverick 17B 128E be self-hosted?+

Both models have the same recorded self-hosting status: supported. Qwen3.5 35B A3B is open weight; Llama 4 Maverick 17B 128E is open weight.

Can Qwen3.5 35B A3B and Llama 4 Maverick 17B 128E understand images?+

Qwen3.5 35B A3B is documented with image input; Llama 4 Maverick 17B 128E is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Qwen3.5 35B A3B or Llama 4 Maverick 17B 128E?+

Neither has a larger sourced maximum output. Qwen3.5 35B A3B is — and Llama 4 Maverick 17B 128E is —.

Do Qwen3.5 35B A3B and Llama 4 Maverick 17B 128E support reasoning and tool use?+

Qwen3.5 35B A3B: reasoning, tool calling, and image input. Llama 4 Maverick 17B 128E: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3.5 35B A3B or Llama 4 Maverick 17B 128E?+

Qwen3.5 35B A3B has 4 sourced provider routes; Llama 4 Maverick 17B 128E has 0, so Qwen3.5 35B A3B has broader tracked availability.

Which offers better value, Qwen3.5 35B A3B or Llama 4 Maverick 17B 128E?+

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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