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Model comparison

Gemini 2.5 Pro vs Ornith-1.0-9B

Data verified

Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

57.25/100
No comparison
DeepReinforce AI
N/A
1 category wins0 category wins

Public leaderboard positions: Gemini 2.5 Pro #70 (Supported); Ornith-1.0-9B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemini 2.5 Pro and Ornith-1.0-9B share 1 comparable benchmark result. 1 of 8 categories are comparable. 23 results are unique to Gemini 2.5 Pro; 6 to Ornith-1.0-9B.

Updated July 23, 2026
Shared results
1
Gemini 2.5 Pro only
23
Ornith-1.0-9B only
6
Comparable categories
1 / 8

Treat this as a split decision. Gemini 2.5 Pro makes more sense if coding is the priority or you need the larger 1M context window; Ornith-1.0-9B is the better fit if you want the cheaper token bill or you want the stronger reasoning-first profile.

Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Gemini 2.5 Pro and Ornith-1.0-9B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $10.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ornith-1.0-9B. That is roughly Infinityx on output cost alone. Ornith-1.0-9B is the reasoning model in the pair, while Gemini 2.5 Pro is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 256K for Ornith-1.0-9B.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Gemini 2.5 Pro and Ornith-1.0-9B
CategoryGemini 2.5 ProΔOrnith-1.0-9B
CodingGemini 2.5 Pro63.8Margin 4.6Ornith-1.0-9B59.2
AgenticGemini 2.5 ProNot measuredMarginNo overlapOrnith-1.0-9B43.1
KnowledgeGemini 2.5 Pro27.4MarginNo overlapOrnith-1.0-9BNot measured
MathGemini 2.5 Pro11.6MarginNo overlapOrnith-1.0-9BNot measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Gemini 2.5 ProB · Ornith-1.0-9B
  1. SWE-bench Verified

    Coding
    Source ↗
    A 63.8%B 69.4%
    Winner: Ornith-1.0-9BΔ 5.6
    SWE-bench Verified: Gemini 2.5 Pro scored 63.8%; Ornith-1.0-9B scored 69.4%. Ornith-1.0-9B wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGemini 2.5 ProOrnith-1.0-9BComparison
Input / output priceUSD per 1M tokensGemini 2.5 Pro$1.25 input / $10 outputOrnith-1.0-9B$0 input / $0 outputOrnith-1.0-9B has the lower combined listed price.
Generation speedtokens per secondGemini 2.5 Pro117 tok/sOrnith-1.0-9BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemini 2.5 Pro21.19 sOrnith-1.0-9BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGemini 2.5 Pro1MOrnith-1.0-9B256KGemini 2.5 Pro lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGemini 2.5 ProOrnith-1.0-9BResult
AA Agentic IndexSource 7.1%Not comparable
τ²-bench resultsSource 54.1%Not comparable
Gert LabsSource 42.01%Not comparable
GDPval-AASource 8.3%Not comparable
GDPval-AASource 665Not comparable
Terminal-Bench 2.0Source 43.1%Not comparable
Claw-EvalSource 63.1%Not comparable
CodingGemini 2.5 Pro wins
BenchmarkGemini 2.5 ProOrnith-1.0-9BResult
SWE-bench VerifiedSource 63.8%69.4%Ornith-1.0-9B leads
Vibe Code BenchSource 0.40%Not comparable
AA Coding IndexSource 33.3%Not comparable
AA-SciCodeSource 42.8%Not comparable
SWE-bench ProSource 42.9%Not comparable
SWE MultilingualSource 52%Not comparable
NL2RepoSource 27.2%Not comparable
Terminal-Bench 2.0Source 43.1%Not comparable
Reasoning
BenchmarkGemini 2.5 ProOrnith-1.0-9BResult
AA-LCRSource 66.0%Not comparable
CritPtSource 2.6%Not comparable
Knowledge
BenchmarkGemini 2.5 ProOrnith-1.0-9BResult
GPQASource 83%Not comparable
HLESource 18.8%Not comparable
Artificial Analysis Intelligence IndexSource 25.8%Not comparable
AA-GPQA DiamondSource 84.4%Not comparable
AA-HLESource 21.1%Not comparable
AA-Omniscience IndexSource -14.3%Not comparable
AA-Omniscience AccuracySource 39.0%Not comparable
AA-Omniscience Hallucination RateSource 87.4%Not comparable
Math
BenchmarkGemini 2.5 ProOrnith-1.0-9BResult
FrontierMath v2 (Tiers 1-3)Source 14.138%Not comparable
FrontierMath v2 (Tier 4)Source 4.167%Not comparable
Multimodal
BenchmarkGemini 2.5 ProOrnith-1.0-9BResult
AA-MMMU-ProSource 74.9%Not comparable
Design Arena WebsiteSource 1197Not comparable
Inst. Following
BenchmarkGemini 2.5 ProOrnith-1.0-9BResult
AA-IFBenchSource 48.7%Not comparable
Frequently Asked Questions (2)

Which is better, Gemini 2.5 Pro or Ornith-1.0-9B?

Gemini 2.5 Pro and Ornith-1.0-9B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for coding, Gemini 2.5 Pro or Ornith-1.0-9B?

Gemini 2.5 Pro has the edge for coding in this comparison, averaging 63.8 versus 59.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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