Long documents
Prompts that approach the documented context limit
MiMo-V2.6-Pro
MiMo-V2.6-Pro has the larger documented context window.
Confidence: documented
MiMo-V2.6-Pro vs Sage-A1.5
Updated October 20, 2026. Rank says MiMo-V2.6-Pro is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Share or export
Decision reading
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 resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 0
- MiMo-V2.6-Pro only
- 14
- Sage-A1.5 only
- 12
- Like-for-like categories
- 0 / 8
Estimated: MiMo-V2.6-Pro and Sage-A1.5. Conditional ranges do not establish rank confidence.How 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.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Sage-A1.5 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
MiMo-V2.6-Pro and Sage-A1.5 are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limitedChat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesRepository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
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.
63.3MiMo-V2.6-Pro54.0Sage-A1.5
Directional only · BenchAlign v5.8
MiMo-V2.6-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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
14 MiMo-V2.6-Pro only
12 Sage-A1.5 only
2 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, 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
Directional only- MiMo-V2.6-Pro
- 67.8
- Estimated · #13/132
- Sage-A1.5
- 57.7
- Estimated · #36/132
- Basis
- BenchAlign v5.8 lane · 9 vs 6 public rows
- Reading
- Directional only
Coding
Directional only- MiMo-V2.6-Pro
- 63.3
- Supported · #13/153
- Sage-A1.5
- 54.0
- Estimated · #34/153
- Basis
- BenchAlign v5.8 lane · 4 vs 3 public rows
- Reading
- Directional only
Reasoning
Not comparable- MiMo-V2.6-Pro
- 82.5
- Unranked · 2 rankable rows
- Sage-A1.5
- 80.6
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- MiMo-V2.6-Pro
- Not ranked
- Sage-A1.5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- MiMo-V2.6-Pro
- 69.4
- Supported · #19/187
- Sage-A1.5
- Not ranked
- Basis
- BenchAlign v5.8 lane · 0 vs 1 public rows
- Reading
- Not comparable
Multilingual
Not comparable- MiMo-V2.6-Pro
- Not ranked
- Sage-A1.5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- MiMo-V2.6-Pro
- Not ranked
- Sage-A1.5
- 91.9
- #22/152
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- MiMo-V2.6-Pro
- Not ranked
- Sage-A1.5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | MiMo-V2.6-Pro | Sage-A1.5 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 67.8Estimated · #13/132 | 57.7Estimated · #36/132 | Directional onlyBenchAlign v5.8 lane · 9 vs 6 public rows | Directional only |
| Coding | 63.3Supported · #13/153 | 54.0Estimated · #34/153 | Directional onlyBenchAlign v5.8 lane · 4 vs 3 public rows | Directional only |
| Reasoning | 82.5Unranked · 2 rankable rows | 80.6Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | 69.4Supported · #19/187 | Not ranked | Not comparableBenchAlign v5.8 lane · 0 vs 1 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 91.9#22/152 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) 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
- MiMo-V2.6-Pro
- $0.00087
- Fits in one request
- Sage-A1.5
- Self-hosted; infrastructure cost varies
- Fits in one request
Sage-A1.5 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- MiMo-V2.6-Pro
- $0.02436
- Fits in one request
- Sage-A1.5
- Self-hosted; infrastructure cost varies
- Fits in one request
Sage-A1.5 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- MiMo-V2.6-Pro
- $0.01812
- Fits in one request
- Sage-A1.5
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Sage-A1.5 has no comparable published API token 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.
SpecificationMiMo-V2.6-ProSage-A1.5
Context window
Maximum documented context; output-token limits may be lower.
MiMo-V2.6-Pro
Sage-A1.5
API model ID
MiMo-V2.6-Pro
Not sourced
Sage-A1.5
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
MiMo-V2.6-Pro
$0.0036 per 1M cached input tokens
Xiaomi MiMo-V2.6 launchSage-A1.5
No comparable hosted API rate
InternScience Sage-A1.5 model cardDocumented inputs
MiMo-V2.6-Pro
Not sourced
Sage-A1.5
Not sourced
Documented outputs
MiMo-V2.6-Pro
Not sourced
Sage-A1.5
Not sourced
Provider availability
MiMo-V2.6-Pro
Not sourced
Sage-A1.5
Not sourced
Reasoning profile
MiMo-V2.6-Pro
Reasoning
Sage-A1.5
Reasoning
Weight access
MiMo-V2.6-Pro
Open Weight
Sage-A1.5
Open Weight
License
MiMo-V2.6-Pro
Open Weight
Sage-A1.5
Open Weight
Release date
MiMo-V2.6-Pro
2026-09-22
Sage-A1.5
2026-10-15
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
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- MiMo-V2.6-Pro has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, MiMo-V2.6-Pro or Sage-A1.5?
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, MiMo-V2.6-Pro or Sage-A1.5?
MiMo-V2.6-Pro scores higher for coding on the public lane, 63.3 to 54. Sage-A1.5 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, MiMo-V2.6-Pro or Sage-A1.5?
MiMo-V2.6-Pro scores higher for agentic tasks on the public lane, 67.8 to 57.7. MiMo-V2.6-Pro and Sage-A1.5 are scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, MiMo-V2.6-Pro or Sage-A1.5?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, MiMo-V2.6-Pro or Sage-A1.5?
MiMo-V2.6-Pro has the larger documented context window: 1M, compared with 262K.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
MiMo-V2.6-Pro
API / mo$979
Self-host / mo$37,843
Break-even2.2B/day
Sage-A1.5
API / mo$0
Self-host / mo$298
Break-even—
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
Toolathlon-Verified
MiMo-V2.6-Pro76.9%SourceSage-A1.5—Not directly comparable
AutomationBench
MiMo-V2.6-Pro53.1%SourceSage-A1.5—Not directly comparable
Agents' Last Exam
MiMo-V2.6-Pro31.6%SourceSage-A1.5—Not directly comparable
Terminal-Bench 4.0
MiMo-V2.6-Pro34.90%SourceSage-A1.5—Not directly comparable
Terminal-Bench 2.1
MiMo-V2.6-Pro89.9%SourceSage-A1.5—Not directly comparable
OSWorld-Verified
MiMo-V2.6-Pro82%SourceSage-A1.5—Not directly comparable
JobBench
MiMo-V2.6-Pro62.0%SourceSage-A1.5—Not directly comparable
CyberGym
MiMo-V2.6-Pro94.0%SourceSage-A1.5—Not directly comparable
ExploitGym
MiMo-V2.6-Pro17.8%SourceSage-A1.5—Not directly comparable
GAIA
MiMo-V2.6-Pro—Sage-A1.595.1%SourceNot directly comparable
BrowseComp
MiMo-V2.6-Pro—Sage-A1.581.7%SourceNot directly comparable
MLE-Bench Lite
MiMo-V2.6-Pro—Sage-A1.565.2%SourceNot directly comparable
HLE w/ tools
MiMo-V2.6-Pro—Sage-A1.555.1%SourceNot directly comparable
VITA-Bench
MiMo-V2.6-Pro—Sage-A1.545.4%SourceNot directly comparable
PinchBench
MiMo-V2.6-Pro—Sage-A1.590.0%SourceNot directly comparable
Coding
DeepSWE
MiMo-V2.6-Pro71.9%SourceSage-A1.5—Not directly comparable
ProgramBench
MiMo-V2.6-Pro26.5%SourceSage-A1.5—Not directly comparable
Terminal-Bench 2.1
MiMo-V2.6-Pro89.9%SourceSage-A1.5—Not directly comparable
Bug Hunt Bench
MiMo-V2.6-Pro22.7 fixesSourceSage-A1.5—Not directly comparable
SciCode
MiMo-V2.6-Pro—Sage-A1.544.3%SourceNot directly comparable
SWE-bench Pro
MiMo-V2.6-Pro—Sage-A1.561.2%SourceNot directly comparable
SWE Multilingual
MiMo-V2.6-Pro—Sage-A1.572.7%SourceNot directly comparable
Reasoning
Knowledge
FrontierScience Research
MiMo-V2.6-Pro—Sage-A1.548.3%SourceNot directly comparable
Instruction following
IFBench
MiMo-V2.6-Pro—Sage-A1.581.6%SourceNot directly comparable
26 public results · 0 shared
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Last updated October 20, 2026