Qwen3.5 35B A3B Base vs Gemini 2.5 Flash

At a Glance

Compare
Gemini 2.5 FlashGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.30Google AI · Aug 29, 2026
Output priceFrom · USD / 1M tokensNot reported$2.50Google AI · Aug 29, 2026
Context windowMaximum documented tokens262K1,049K
Model facts checkedAug 28, 2026View model evidence →Aug 29, 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-A3B-BaseGemini 2.5 Flash
DeveloperQwenGoogle DeepMind
FamilyQwen3 5 35b A3b BaseGemini 2 5
ModelQwen3.5-35B-A3B-BaseGemini 2.5 Flash
VersionQwen3.5-35B-A3B-BaseGemini 2.5 Flash
Lifecycleactiveactive
ReleasedUnknownUnknown
Knowledge cutoffUnknown2025-01-01
Input modalitiesText, ImageText, Image, Video, Audio
Output modalitiesTextText
Context window262K1,049K
Total parameters36BUnknown
Active parameters3BUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableUnknownYes
Self-hostableYesNo
Provider accessUnknownGoogle AI (Standard), Google Gemini (Standard)
Capabilitieschat, generation, toolschat, generation, reasoning, tools

Qwen3.5 35B A3B Base Capabilities

chatgenerationtools
Serving providers0
Canonical IDQwen/Qwen3.5-35B-A3B-Base

Gemini 2.5 Flash Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDgoogle-deepmind/gemini-2.5-flash

Primary Evidence

Sources and Freshness

Questions

Qwen3.5 35B A3B Base vs Gemini 2.5 Flash FAQs

Is Qwen3.5 35B A3B Base or Gemini 2.5 Flash better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 35B A3B Base and Gemini 2.5 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Qwen3.5 35B A3B Base or Gemini 2.5 Flash?+

Only Gemini 2.5 Flash has a directly sourced input price: $0.30 per million tokens. Only Gemini 2.5 Flash has a directly sourced output price: $2.50 per million tokens.

Which has a larger context window, Qwen3.5 35B A3B Base or Gemini 2.5 Flash?+

Gemini 2.5 Flash has the larger sourced context window. Qwen3.5 35B A3B Base supports 262K and Gemini 2.5 Flash supports 1,049K.

Which performs better in benchmarks, Qwen3.5 35B A3B Base or Gemini 2.5 Flash?+

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 Base or Gemini 2.5 Flash be self-hosted?+

Qwen3.5 35B A3B Base is the only model in this pair currently marked as self-hostable. Qwen3.5 35B A3B Base is open weight; Gemini 2.5 Flash is not marked open weight.

Can Qwen3.5 35B A3B Base and Gemini 2.5 Flash understand images?+

Qwen3.5 35B A3B Base is documented with image input; Gemini 2.5 Flash is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Qwen3.5 35B A3B Base or Gemini 2.5 Flash?+

Neither has a larger sourced maximum output. Qwen3.5 35B A3B Base is — and Gemini 2.5 Flash is 66K.

Do Qwen3.5 35B A3B Base and Gemini 2.5 Flash support reasoning and tool use?+

Qwen3.5 35B A3B Base: tool calling and image input. Gemini 2.5 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3.5 35B A3B Base or Gemini 2.5 Flash?+

Qwen3.5 35B A3B Base has 0 sourced provider routes; Gemini 2.5 Flash has 2, so Gemini 2.5 Flash has broader tracked availability.

Which offers better value, Qwen3.5 35B A3B Base or Gemini 2.5 Flash?+

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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