Agentic work
Tool use, computer use, and multi-step task completion
Gemini 3 Flash
Gemini 3 Flash leads on the public agentic lane, 31.7 to 29.1, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Gemini 3 Flash vs MiniMax M2.7
Updated September 29, 2026. Rank says Gemini 3 Flash is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Share or export
Decision reading
Gemini 3 Flash has the higher public score estimate, 55.5 versus 47.85, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 8 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 8
- Gemini 3 Flash only
- 3
- MiniMax M2.7 only
- 15
- Like-for-like categories
- 3 / 8
Supported: Gemini 3 Flash and MiniMax M2.7How 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.
Long documents
Prompts that approach the documented context limit
Gemini 3 Flash
Gemini 3 Flash has the larger documented context window.
Confidence: documentedChat turn cost
1K fresh input + 500 output tokens
MiniMax M2.7
MiniMax M2.7 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
MiniMax M2.7
MiniMax M2.7 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
No clear pick
The like-for-like coding result is a practical tie on the public lane (within 0.5 points).
Confidence: limitedCache-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. MiniMax M2.7 does not fit this workload in one request. MiniMax M2.7 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
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.
36.4Gemini 3 Flash36.0MiniMax M2.7
Like-for-like · BenchAlign v5.7
The like-for-like coding row is a practical tie.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 Gemini 3 Flash only
8 Shared
15 MiniMax M2.7 only
1 category rests 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.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
MMLU-Pro (Vals)Knowledge
Normalized gap 8.2Gemini 3 Flash:88.6%MiniMax M2.7:80.4%LiveCodeBench (Vals)Coding
Normalized gap 5.7Gemini 3 Flash:85.6%MiniMax M2.7:79.9%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.7 lane for agentic, coding, 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.
Agentic
Like-for-like- Gemini 3 Flash
- 31.7
- Supported · #76/117
- MiniMax M2.7
- 29.1
- Supported · #82/117
- Basis
- BenchAlign v5.7 lane · 4 vs 7 public rows
- Reading
- Gemini 3 Flash leads · intervals overlap
Coding
Like-for-like- Gemini 3 Flash
- 36.4
- Supported · #74/143
- MiniMax M2.7
- 36.0
- Supported · #77/143
- Basis
- BenchAlign v5.7 lane · 3 vs 11 public rows
- Reading
- Practical tie
Knowledge
Like-for-like- Gemini 3 Flash
- 54.3
- Supported · #47/169
- MiniMax M2.7
- 43.0
- Supported · #86/169
- Basis
- BenchAlign v5.7 lane · 2 vs 4 public rows
- Reading
- Gemini 3 Flash leads · intervals overlap
Instruction following
Directional only- Gemini 3 Flash
- 64.7
- #70/124
- MiniMax M2.7
- 91.6
- #10/124
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Gemini 3 Flash
- 60.3
- Unranked · 2 rankable rows
- MiniMax M2.7
- 76.1
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 3 Flash
- 76.9
- Unranked · 1 rankable row
- MiniMax M2.7
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3 Flash
- Not ranked
- MiniMax M2.7
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3 Flash
- 50.0
- Unranked · 2 rankable rows
- MiniMax M2.7
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
| Category | Gemini 3 Flash | MiniMax M2.7 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 31.7Supported · #76/117 | 29.1Supported · #82/117 | Like-for-likeBenchAlign v5.7 lane · 4 vs 7 public rows | Gemini 3 Flash leads · intervals overlap |
| Coding | 36.4Supported · #74/143 | 36.0Supported · #77/143 | Like-for-likeBenchAlign v5.7 lane · 3 vs 11 public rows | Practical tie |
| Knowledge | 54.3Supported · #47/169 | 43.0Supported · #86/169 | Like-for-likeBenchAlign v5.7 lane · 2 vs 4 public rows | Gemini 3 Flash leads · intervals overlap |
| Instruction following | 64.7#70/124 | 91.6#10/124 | Directional onlyProvisional lane · 0 vs 0 weighted rows | Directional only |
| Reasoning | 60.3Unranked · 2 rankable rows | 76.1Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 76.9Unranked · 1 rankable row | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 50.0Unranked · 2 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, and knowledge denominators (BenchAlign v5.7) 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 3 Flash
- $0.002
- Fits in one request
- MiniMax M2.7
- $0.0009
- Fits in one request
MiniMax M2.7 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Gemini 3 Flash
- $0.034
- Fits in one request
- MiniMax M2.7
- $0.0186
- Fits in one request
MiniMax M2.7 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 Flash
- $0.05
- Fits in one request
- MiniMax M2.7
- $0.078
- Does not fit in one request
- Cached input priced at the published list-input rate
MiniMax M2.7 does not fit this workload in one request. MiniMax M2.7 has no published cached-input rate, so cached tokens use its listed input rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGemini 3 FlashMiniMax M2.7
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3 Flash
MiniMax M2.7
200K
API model ID
Gemini 3 Flash
gemini-3-flash-preview
Google Gemini API pricingMiniMax M2.7
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemini 3 Flash
$0.05 per 1M cached input tokens
Google Gemini API pricingMiniMax M2.7
Not published
Documented inputs
Gemini 3 Flash
Not sourced
MiniMax M2.7
Not sourced
Documented outputs
Gemini 3 Flash
Not sourced
MiniMax M2.7
Not sourced
Provider availability
Gemini 3 Flash
Not sourced
MiniMax M2.7
Not sourced
Reasoning profile
Gemini 3 Flash
Non-Reasoning
MiniMax M2.7
Non-Reasoning
Weight access
Gemini 3 Flash
Proprietary
MiniMax M2.7
Open Weight
License
Gemini 3 Flash
Proprietary
MiniMax M2.7
Open Weight
Release date
Gemini 3 Flash
2025-12-01
MiniMax M2.7
2026-03-18
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
- Gemini 3 Flash has the higher public score estimate, 55.5 versus 47.85, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.034 vs $0.0186. Cache-heavy agent loop: $0.05 vs $0.078.
- Context tradeoff
- Gemini 3 Flash has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Gemini 3 Flash or MiniMax M2.7?
Gemini 3 Flash has the higher public score estimate, 55.5 versus 47.85, 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 3 Flash or MiniMax M2.7?
The like-for-like coding row is a practical tie on the public lane, 36.4 against 36, inside the 0.5-point band BenchLM treats as level.
Which is better for agentic tasks, Gemini 3 Flash or MiniMax M2.7?
Gemini 3 Flash leads the public agentic tasks lane, 31.7 to 29.1, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Gemini 3 Flash or MiniMax M2.7?
For the stated presets, chat costs $0.002 on Gemini 3 Flash and $0.0009 on MiniMax M2.7; repository review costs $0.034 and $0.0186; the cache-heavy agent loop costs $0.05 and $0.078. MiniMax M2.7 does not fit this workload in one request. MiniMax M2.7 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Gemini 3 Flash or MiniMax M2.7?
Gemini 3 Flash has the larger documented context window: 1M, compared with 200K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence26 rows
Agentic
Claw-Eval
Shared sourceGemini 3 Flash49.2%MiniMax M2.748.7%Gemini 3 Flash leads this result
Gert Labs
Shared sourceGemini 3 Flash56.63%MiniMax M2.740.40%Gemini 3 Flash leads this result
JobBench
Gemini 3 Flash11.4%SourceMiniMax M2.7—Not directly comparable
Terminal-Bench 2.1 (Vals)
Gemini 3 Flash53.9%SourceMiniMax M2.748.7%SourceGemini 3 Flash leads this result
Terminal-Bench 2.0
Gemini 3 Flash—MiniMax M2.757%SourceNot directly comparable
Toolathlon
Gemini 3 Flash—MiniMax M2.746.3%SourceNot directly comparable
MLE-Bench Lite
Gemini 3 Flash—MiniMax M2.766.6%SourceNot directly comparable
MM-ClawBench
Gemini 3 Flash—MiniMax M2.762.7%SourceNot directly comparable
Coding
Vibe Code Bench
Shared sourceGemini 3 Flash20.20%MiniMax M2.727.04%MiniMax M2.7 leads this result
LiveCodeBench (Vals)
Gemini 3 Flash85.6%SourceMiniMax M2.779.9%SourceGemini 3 Flash leads this result
SWE-bench (Vals)
Gemini 3 Flash75.0%SourceMiniMax M2.773.8%SourceGemini 3 Flash leads this result
SWE-bench Verified*
Gemini 3 Flash—MiniMax M2.775.4%SourceNot directly comparable
SWE-bench Pro
Gemini 3 Flash—MiniMax M2.756.2%SourceNot directly comparable
SWE-Rebench
Gemini 3 Flash—MiniMax M2.751.9%SourceNot directly comparable
SWE Multilingual
Gemini 3 Flash—MiniMax M2.776.5%SourceNot directly comparable
Multi-SWE Bench
Gemini 3 Flash—MiniMax M2.752.7%SourceNot directly comparable
VIBE-Pro
Gemini 3 Flash—MiniMax M2.755.6%SourceNot directly comparable
NL2Repo
Gemini 3 Flash—MiniMax M2.739.8%SourceNot directly comparable
React Native Evals
Gemini 3 Flash—MiniMax M2.771.4%SourceNot directly comparable
Knowledge
GPQA Diamond (Vals)
Gemini 3 Flash87.9%SourceMiniMax M2.786.6%SourceGemini 3 Flash leads this result
MMLU-Pro (Vals)
Gemini 3 Flash88.6%SourceMiniMax M2.780.4%SourceGemini 3 Flash leads this result
GPQA-D
Gemini 3 Flash—MiniMax M2.787.0%SourceNot directly comparable
MMLU-Pro (Arcee)
Gemini 3 Flash—MiniMax M2.780.8%SourceNot directly comparable
Math
26 public results · 8 shared
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Last updated September 29, 2026