Gemini 2.5 Pro vs Qwen3 Coder Flash

At a Glance

Compare
Gemini 2.5 ProGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$1.25Google AI · Aug 29, 2026$0.195Openrouter · Sep 23, 2026
Output priceFrom · USD / 1M tokens$10.00Google AI · Aug 29, 2026$0.975Openrouter · Sep 23, 2026
Context windowMaximum documented tokens1,049K1,000K
Model facts checkedAug 29, 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

FieldGemini 2.5 ProQwen3 Coder Flash
DeveloperGoogle DeepMindQwen
FamilyGemini 2 5Qwen3 Coder
ModelGemini 2.5 ProQwen3 Coder Flash
VersionGemini 2.5 ProQwen3 Coder Flash
Lifecycleactiveactive
ReleasedUnknown2025-07-28
Knowledge cutoff2025-01-01Unknown
Input modalitiesText, Image, Video, Audio, DocumentText
Output modalitiesTextText
Context window1,049K1,000K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessGoogle AI (Standard), Google Gemini (Standard)Alibaba Cloud Model Studio (Standard), Openrouter (Standard)
Capabilitieschat, generation, reasoning, toolsagents, chat, generation, reasoning, structured_outputs, tools

Gemini 2.5 Pro Capabilities

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

Qwen3 Coder Flash Capabilities

agentschatgenerationreasoningstructured outputstools
Serving providers2
Canonical IDqwen/qwen3-coder-flash

Primary Evidence

Sources and Freshness

Questions

Gemini 2.5 Pro vs Qwen3 Coder Flash FAQs

Is Gemini 2.5 Pro or Qwen3 Coder Flash better for coding?+

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

Which is cheaper, Gemini 2.5 Pro or Qwen3 Coder Flash?+

Gemini 2.5 Pro is $1.25 and Qwen3 Coder Flash is $0.195 per million tokens, so Qwen3 Coder Flash is cheaper on this metric. Gemini 2.5 Pro is $10.00 and Qwen3 Coder Flash is $0.975 per million tokens, so Qwen3 Coder Flash is cheaper on this metric.

Which has a larger context window, Gemini 2.5 Pro or Qwen3 Coder Flash?+

Gemini 2.5 Pro has the larger sourced context window. Gemini 2.5 Pro supports 1,049K and Qwen3 Coder Flash supports 1,000K.

Which performs better in benchmarks, Gemini 2.5 Pro or Qwen3 Coder Flash?+

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

Can Gemini 2.5 Pro or Qwen3 Coder Flash be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Gemini 2.5 Pro is not marked open weight; Qwen3 Coder Flash is not marked open weight.

Can Gemini 2.5 Pro and Qwen3 Coder Flash understand images?+

Gemini 2.5 Pro is documented with image input; Qwen3 Coder Flash is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini 2.5 Pro or Qwen3 Coder Flash?+

Neither has a larger sourced maximum output. Gemini 2.5 Pro is 66K and Qwen3 Coder Flash is —.

Do Gemini 2.5 Pro and Qwen3 Coder Flash support reasoning and tool use?+

Gemini 2.5 Pro: reasoning, tool calling, and image input. Qwen3 Coder Flash: reasoning and tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini 2.5 Pro or Qwen3 Coder Flash?+

Gemini 2.5 Pro has 2 sourced provider routes; Qwen3 Coder Flash has 2, a tie.

Which offers better value, Gemini 2.5 Pro or Qwen3 Coder 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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