Long documents
Prompts that approach the documented context limit
Gemini 3 Pro
Gemini 3 Pro has the larger documented context window.
Confidence: documented
Gemini 2.5 Pro vs Gemini 3 Pro
Updated November 13, 2026. Rank says Gemini 3 Pro is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Share or export
Decision reading
Gemini 3 Pro has the higher public score estimate, 58.35 versus 48.78, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- API price per 1M tokens
Gemini 2.5 Pro: $1.25 input / $10 output
Gemini 3 Pro: $2 input / $12 output
- Context window
Gemini 2.5 Pro: 1M
Gemini 3 Pro: 2M
- Released
Gemini 2.5 Pro: March 1, 2025
Gemini 3 Pro: November 18, 2025
- Shared results
- 3
- Gemini 2.5 Pro only
- 6
- Gemini 3 Pro only
- 29
- Like-for-like categories
- 1 / 8
Supported: Gemini 2.5 Pro and Gemini 3 ProHow the comparison works
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Chat turn cost
1K fresh input + 500 output tokens
Gemini 2.5 Pro
Gemini 2.5 Pro has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Gemini 2.5 Pro
Gemini 2.5 Pro has the lower estimated token cost for this stated workload. Gemini 3 Pro has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Gemini 2.5 Pro
Gemini 2.5 Pro has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Gemini 3 Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemini 3 Pro is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
21.9Gemini 2.5 Pro43.3Gemini 3 Pro
Directional only · BenchAlign v5.8
Gemini 3 Pro has the higher coding point estimate. Conditional score ranges do not establish rank confidence.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
Or describe your own job
The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.
Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.
We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
6 Gemini 2.5 Pro only
3 Shared
29 Gemini 3 Pro only
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, reasoning, multimodal, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Knowledge
Like-for-like- Gemini 2.5 Pro
- 44.8
- Supported · #97/180
- Gemini 3 Pro
- 62.1
- Supported · #40/180
- Basis
- BenchAlign v5.8 lane · 2 vs 2 public rows
- Reading
- Gemini 3 Pro leads · intervals overlap
Coding
Directional only- Gemini 2.5 Pro
- 21.9
- Supported · #129/162
- Gemini 3 Pro
- 43.3
- Estimated · #69/162
- Basis
- BenchAlign v5.8 lane · 3 vs 4 public rows
- Reading
- Directional only
Reasoning
Directional only- Gemini 2.5 Pro
- 37.1
- Estimated · #100/160
- Gemini 3 Pro
- 48.7
- Supported · #54/160
- Basis
- BenchAlign v5.8 lane · 0 vs 2 public rows
- Reading
- Directional only
Instruction following
Directional only- Gemini 2.5 Pro
- 57.8
- #90/157
- Gemini 3 Pro
- 86.1
- #48/157
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Directional only
Agentic
Not comparable- Gemini 2.5 Pro
- 28.8
- Estimated · #110/135
- Gemini 3 Pro
- Not ranked
- Basis
- BenchAlign v5.8 lane · 1 vs 2 public rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 2.5 Pro
- Not ranked
- Gemini 3 Pro
- 58.7
- Estimated · #40/67
- Basis
- BenchAlign v5.8 lane · 0 vs 22 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 2.5 Pro
- Not ranked
- Gemini 3 Pro
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 2.5 Pro
- 33.2
- Unranked · 3 rankable rows
- Gemini 3 Pro
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
| Category | Gemini 2.5 Pro | Gemini 3 Pro | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 44.8Supported · #97/180 | 62.1Supported · #40/180 | Like-for-likeBenchAlign v5.8 lane · 2 vs 2 public rows | Gemini 3 Pro leads · intervals overlap |
| Coding | 21.9Supported · #129/162 | 43.3Estimated · #69/162 | Directional onlyBenchAlign v5.8 lane · 3 vs 4 public rows | Directional only |
| Reasoning | 37.1Estimated · #100/160 | 48.7Supported · #54/160 | Directional onlyBenchAlign v5.8 lane · 0 vs 2 public rows | Directional only |
| Instruction following | 57.8#90/157 | 86.1#48/157 | Directional onlyProvisional lane · 0 vs 0 weighted rows | Directional only |
| Agentic | 28.8Estimated · #110/135 | Not ranked | Not comparableBenchAlign v5.8 lane · 1 vs 2 public rows | Not comparable |
| Multimodal | Not ranked | 58.7Estimated · #40/67 | Not comparableBenchAlign v5.8 lane · 0 vs 22 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 33.2Unranked · 3 rankable rows | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Gemini 2.5 Pro
- $0.00625
- Fits in one request
- Gemini 3 Pro
- $0.008
- Fits in one request
Gemini 2.5 Pro has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Gemini 2.5 Pro
- $0.0925
- Fits in one request
- Gemini 3 Pro
- $0.136
- Fits in one request
Gemini 2.5 Pro has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Gemini 2.5 Pro
- $0.15
- Fits in one request
- Gemini 3 Pro
- $0.56
- Fits in one request
- Cached input priced at the published list-input rate
Gemini 2.5 Pro has the lower modeled cost
Gemini 3 Pro has no published cached-input rate, so cached tokens use its listed input rate.
Your workload
Enter a month of tokens to price it at both models’ listed API rates.
- Gemini 2.5 Pro
- $32.50
- per month
- Gemini 3 Pro
- $44.00
- per month
Standard listed rates, no batch or volume discounts.
Cached input falls back to the list input rate only where a cached rate is unpublished
Price against score, among all priced models
Overall score against output price per 1M tokens, one model per family. Pricing as of November 12, 2026.
Gemini 2.5 ProGemini 3 Pro
- 34 models score at least as high as Gemini 2.5 Pro for the same price or less. The nearest is Gemini 4 Carbon (score 89.2, also $10.00 per 1M output tokens).
- 17 models score at least as high as Gemini 3 Pro for the same price or less. The nearest is Gemini 3.1 Pro (score 63.1, also $12.00 per 1M output tokens).
Gray dots are the other priced models. The dark step line is the efficiency frontier: for a model under it, another model costs no more and scores at least as high.
See Gemini 2.5 Pro on the full price vs performance chartSpecification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGemini 2.5 ProGemini 3 Pro
Context window
Maximum documented context; output-token limits may be lower.
Gemini 2.5 Pro
Gemini 3 Pro
2M
API model ID
Gemini 2.5 Pro
gemini-2.5-pro
Google Gemini API pricingGemini 3 Pro
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemini 2.5 Pro
$0.125 per 1M cached input tokens
Google Gemini API pricingGemini 3 Pro
Not published
Documented inputs
Gemini 2.5 Pro
text, image, video, audio, pdf
Gemini API model page for gemini-2.5-proGemini 3 Pro
text, image, video, audio, pdf
Gemini API model page for gemini-3-pro-previewDocumented outputs
Gemini 2.5 Pro
Gemini 3 Pro
Provider availability
Gemini 2.5 Pro
Not sourced
Gemini 3 Pro
Not sourced
Reasoning profile
Gemini 2.5 Pro
Non-Reasoning
Gemini 3 Pro
Non-Reasoning
Weight access
Gemini 2.5 Pro
Proprietary
Gemini 3 Pro
Proprietary
License
Gemini 2.5 Pro
Proprietary
Gemini 3 Pro
Proprietary
Release date
Gemini 2.5 Pro
2025-03-01
Gemini 3 Pro
2025-11-18
If you already use one of these models
- Deployment change
- Both entries list Google as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- Gemini 3 Pro has the higher public score estimate, 58.35 versus 48.78, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.0925 vs $0.136. Cache-heavy agent loop: $0.15 vs $0.56.
- Context tradeoff
- Gemini 3 Pro has the larger documented window (2M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Gemini 2.5 Pro or Gemini 3 Pro?
Gemini 3 Pro has the higher public score estimate, 58.35 versus 48.78, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Gemini 2.5 Pro or Gemini 3 Pro?
Gemini 3 Pro scores higher for coding on the public lane, 43.3 to 21.9. Gemini 3 Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Gemini 2.5 Pro or Gemini 3 Pro?
Gemini 3 Pro is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Gemini 2.5 Pro or Gemini 3 Pro?
For the stated presets, chat costs $0.00625 on Gemini 2.5 Pro and $0.008 on Gemini 3 Pro; repository review costs $0.0925 and $0.136; the cache-heavy agent loop costs $0.15 and $0.56. Gemini 3 Pro has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Gemini 2.5 Pro or Gemini 3 Pro?
Gemini 3 Pro has the larger documented context window: 2M, compared with 1M.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence38 rows
Agentic
Gert Labs
Shared sourceGemini 2.5 Pro42.01%Gemini 3 Pro63.23%Gemini 3 Pro leads this result
JobBench
Gemini 2.5 Pro—Gemini 3 Pro11.4%SourceNot directly comparable
Coding
SWE-bench Verified
Gemini 2.5 Pro63.8%SourceGemini 3 Pro—Not directly comparable
Vibe Code Bench
Shared sourceGemini 2.5 Pro0.40%Gemini 3 Pro14.30%Gemini 3 Pro leads this result
SWE-bench (Vals)
Gemini 2.5 Pro54.4%SourceGemini 3 Pro76.4%SourceGemini 3 Pro leads this result
LiveCodeBench (Vals)
Gemini 2.5 Pro—Gemini 3 Pro86.4%SourceNot directly comparable
PostTrainBench v1
Gemini 2.5 Pro—Gemini 3 Pro18.1%SourceNot directly comparable
Reasoning
Multimodal
MMMU
Gemini 2.5 Pro—Gemini 3 Pro87.2%SourceNot directly comparable
MMMU-Pro
Gemini 2.5 Pro—Gemini 3 Pro81%SourceNot directly comparable
RealWorldQA
Gemini 2.5 Pro—Gemini 3 Pro83.3%SourceNot directly comparable
OmniDocBench 1.5
Gemini 2.5 Pro—Gemini 3 Pro88.5%SourceNot directly comparable
Video-MME (with subtitle)
Gemini 2.5 Pro—Gemini 3 Pro88.4%SourceNot directly comparable
Video-MME (w/o subtitle)
Gemini 2.5 Pro—Gemini 3 Pro87.7%SourceNot directly comparable
MathVision
Gemini 2.5 Pro—Gemini 3 Pro86.6%SourceNot directly comparable
We-Math
Gemini 2.5 Pro—Gemini 3 Pro86.9%SourceNot directly comparable
DynaMath
Gemini 2.5 Pro—Gemini 3 Pro85.1%SourceNot directly comparable
SimpleVQA
Gemini 2.5 Pro—Gemini 3 Pro73.2%SourceNot directly comparable
MMLongBench-Doc
Gemini 2.5 Pro—Gemini 3 Pro60.5%SourceNot directly comparable
CC-OCR
Gemini 2.5 Pro—Gemini 3 Pro79.0%SourceNot directly comparable
AI2D_TEST
Gemini 2.5 Pro—Gemini 3 Pro94.1%SourceNot directly comparable
CountBench
Gemini 2.5 Pro—Gemini 3 Pro97.3%SourceNot directly comparable
RefCOCO (avg)
Gemini 2.5 Pro—Gemini 3 Pro84.1%SourceNot directly comparable
ODINW13
Gemini 2.5 Pro—Gemini 3 Pro46.3%SourceNot directly comparable
ERQA
Gemini 2.5 Pro—Gemini 3 Pro70.5%SourceNot directly comparable
VideoMMMU
Gemini 2.5 Pro—Gemini 3 Pro87.6%SourceNot directly comparable
MLVU (M-Avg)
Gemini 2.5 Pro—Gemini 3 Pro83.0%SourceNot directly comparable
ScreenSpot Pro
Gemini 2.5 Pro—Gemini 3 Pro72.7%SourceNot directly comparable
CharXiv
Gemini 2.5 Pro—Gemini 3 Pro81.4%SourceNot directly comparable
V*
Gemini 2.5 Pro—Gemini 3 Pro88.0%SourceNot directly comparable
Knowledge
Math
38 public results · 3 shared
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Last updated November 13, 2026