Agentic
Not comparable- Gemini 3.5 Flash
- 77.2
- GPT Realtime 2
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Model comparison
Gemini 3.5 Flash vs GPT Realtime 2
Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.
0 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Long documents
Prompts that approach the documented context limit
Gemini 3.5 Flash
Gemini 3.5 Flash has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Gemini 3.5 Flash
Gemini 3.5 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Gemini 3.5 Flash
Gemini 3.5 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. GPT Realtime 2 does not fit this workload in one request.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
22 Gemini 3.5 Flash only
- Shared results
- 0
- Gemini 3.5 Flash only
- 22
- GPT Realtime 2 only
- 0
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Not comparable- Gemini 3.5 Flash
- 55.1
- GPT Realtime 2
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Gemini 3.5 Flash
- 74.7
- GPT Realtime 2
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Gemini 3.5 Flash
- 40.2
- GPT Realtime 2
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.5 Flash
- 32.9
- GPT Realtime 2
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.5 Flash
- Not measured
- GPT Realtime 2
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 3.5 Flash
- 83.8
- GPT Realtime 2
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.5 Flash
- Not measured
- GPT Realtime 2
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Gemini 3.5 Flash | GPT Realtime 2 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 77.2 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Coding | 55.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Reasoning | 74.7 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Knowledge | 40.2 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 32.9 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 83.8 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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.
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 3.5 Flash
- $0.006
- Fits in one request
- GPT Realtime 2
- $0.016
- Fits in one request
Gemini 3.5 Flash has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Gemini 3.5 Flash
- $0.102
- Fits in one request
- GPT Realtime 2
- $0.272
- Fits in one request
Gemini 3.5 Flash 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 3.5 Flash
- $0.15
- Fits in one request
- GPT Realtime 2
- $0.4
- Does not fit in one request
GPT Realtime 2 does not fit this workload in one request.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGemini 3.5 FlashGPT Realtime 2
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.5 Flash
GPT Realtime 2
API model ID
Gemini 3.5 Flash
gemini-3.5-flash
Google Gemini API pricingGPT Realtime 2
gpt-realtime-2
OpenAI model documentationCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemini 3.5 Flash
$0.15 per 1M cached input tokens
Google Gemini API pricingGPT Realtime 2
$0.4 per 1M cached input tokens
OpenAI model documentationDocumented inputs
Gemini 3.5 Flash
Not sourced
GPT Realtime 2
Not sourced
Documented outputs
Gemini 3.5 Flash
Not sourced
GPT Realtime 2
Not sourced
Provider availability
Gemini 3.5 Flash
Not sourced
GPT Realtime 2
Not sourced
Reasoning profile
Gemini 3.5 Flash
Reasoning
GPT Realtime 2
Non-Reasoning
Weight access
Gemini 3.5 Flash
Proprietary
GPT Realtime 2
Proprietary
License
Gemini 3.5 Flash
Proprietary
GPT Realtime 2
Proprietary
Release date
Gemini 3.5 Flash
2026-05-19
GPT Realtime 2
Not sourced
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- Repository review: $0.102 vs $0.272. Cache-heavy agent loop: $0.15 vs $0.4.
- Context tradeoff
- Gemini 3.5 Flash has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence22 rows
Agentic
Terminal-Bench 2.0
Gemini 3.5 Flash76.2%SourceGPT Realtime 2—Not directly comparable
MCP Atlas
Gemini 3.5 Flash83.6%SourceGPT Realtime 2—Not directly comparable
Toolathlon
Gemini 3.5 Flash56.5%SourceGPT Realtime 2—Not directly comparable
OSWorld-Verified
Gemini 3.5 Flash78.4%SourceGPT Realtime 2—Not directly comparable
Finance Agent v2
Gemini 3.5 Flash57.9%SourceGPT Realtime 2—Not directly comparable
Gert Labs
Gemini 3.5 Flash61.85%SourceGPT Realtime 2—Not directly comparable
ResearchClawBench
Gemini 3.5 Flash18.0%SourceGPT Realtime 2—Not directly comparable
Coding
Terminal-Bench 2.0
Gemini 3.5 Flash76.2%SourceGPT Realtime 2—Not directly comparable
SWE-bench Pro
Gemini 3.5 Flash55.1%SourceGPT Realtime 2—Not directly comparable
Vibe Code Bench
Gemini 3.5 Flash48.68%SourceGPT Realtime 2—Not directly comparable
cursorBench31
Gemini 3.5 Flash49.8%SourceGPT Realtime 2—Not directly comparable
cursorBench32
Gemini 3.5 Flash48.8%SourceGPT Realtime 2—Not directly comparable
Reasoning
Knowledge
Math
Multimodal
Frequently asked questions
Which is better, Gemini 3.5 Flash or GPT Realtime 2?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Gemini 3.5 Flash or GPT Realtime 2?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Gemini 3.5 Flash or GPT Realtime 2?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Gemini 3.5 Flash or GPT Realtime 2?
For the stated presets, chat costs $0.006 on Gemini 3.5 Flash and $0.016 on GPT Realtime 2; repository review costs $0.102 and $0.272; the cache-heavy agent loop costs $0.15 and $0.4. GPT Realtime 2 does not fit this workload in one request.
Which has the larger context window, Gemini 3.5 Flash or GPT Realtime 2?
Gemini 3.5 Flash has the larger documented context window: 1M, compared with 128K.
Related comparisons
Last updated August 4, 2026
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