Gemini 2.5 Pro vs Hy3

At a Glance

Compare
Gemini 2.5 ProGoogle DeepMind
Hy3Tencent
Pricing and Limits
Input priceFrom · USD / 1M tokens$1.25Google AI · Aug 29, 2026$0.13Deepinfra · Sep 23, 2026
Output priceFrom · USD / 1M tokens$10.00Google AI · Aug 29, 2026$0.528Openrouter · Sep 23, 2026
Context windowMaximum documented tokens1,049K262K
Model facts checkedAug 29, 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 →
BenchmarkGemini 2.5 ProHy3
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,457.77100% of row best · rating · gemini-2.5-pro; 95% CI [1455.30542635, 1460.23799206]; votes 122554; rank 361,440.5899% of row best · rating · hy3; 95% CI [1433.39024152, 1447.77894384]; votes 8047; rank 65
Overall ResultCounted from the protocol-matched rows above1 benchmark winNo overall winner0 benchmark winsNo overall winner

Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.

Side-by-Side Facts

FieldGemini 2.5 ProHy3
DeveloperGoogle DeepMindTencent
FamilyGemini 2 5Hy3
ModelGemini 2.5 ProHy3
VersionGemini 2.5 ProHy3
Lifecycleactiveactive
ReleasedUnknownUnknown
Knowledge cutoff2025-01-01Unknown
Input modalitiesText, Image, Video, Audio, DocumentText
Output modalitiesTextText
Context window1,049K262K
Total parametersUnknown298.8B
Active parametersUnknown21B
LicenseUnknownapache-2.0
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessGoogle AI (Standard), Google Gemini (Standard)Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)
Capabilitieschat, generation, reasoning, toolschat, generation, tools

Gemini 2.5 Pro Capabilities

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

Hy3 Capabilities

chatgenerationtools
Serving providers3
Canonical IDtencent/Hy3

Primary Evidence

Sources and Freshness

Questions

Gemini 2.5 Pro vs Hy3 FAQs

Is Gemini 2.5 Pro or Hy3 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 2.5 Pro and Hy3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini 2.5 Pro or Hy3?+

Gemini 2.5 Pro is $1.25 and Hy3 is $0.13 per million tokens, so Hy3 is cheaper on this metric. Gemini 2.5 Pro is $10.00 and Hy3 is $0.528 per million tokens, so Hy3 is cheaper on this metric.

Which has a larger context window, Gemini 2.5 Pro or Hy3?+

Gemini 2.5 Pro has the larger sourced context window. Gemini 2.5 Pro supports 1,049K and Hy3 supports 262K.

Which performs better in benchmarks, Gemini 2.5 Pro or Hy3?+

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 Hy3 be self-hosted?+

Hy3 is the only model in this pair currently marked as self-hostable. Gemini 2.5 Pro is not marked open weight; Hy3 is open weight.

Can Gemini 2.5 Pro and Hy3 understand images?+

Gemini 2.5 Pro is documented with image input; Hy3 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini 2.5 Pro or Hy3?+

Neither has a larger sourced maximum output. Gemini 2.5 Pro is 66K and Hy3 is —.

Do Gemini 2.5 Pro and Hy3 support reasoning and tool use?+

Gemini 2.5 Pro: reasoning, tool calling, and image input. Hy3: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini 2.5 Pro or Hy3?+

Gemini 2.5 Pro has 2 sourced provider routes; Hy3 has 3, so Hy3 has broader tracked availability.

Which offers better value, Gemini 2.5 Pro or Hy3?+

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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