Agentic
Like-for-like- Inkling-Small
- 36.9
- Supported · #128/152
- MiniMax M3
- 42.1
- Supported · #107/152
- Basis
- BenchAlign lane · 5 vs 9 public rows
- Reading
- MiniMax M3 leads · intervals overlap
Inkling-Small vs MiniMax M3
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
MiniMax M3 has the higher public score estimate, 61.55 versus 59.25, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
12 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Agentic work
Tool use, computer use, and multi-step task completion
MiniMax M3
MiniMax M3 leads on the public agentic lane, 42.1 to 36.9, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
MiniMax M3
MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
MiniMax M3
MiniMax M3 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 M3
MiniMax M3 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
MiniMax M3 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
13 Inkling-Small only
12 Shared
15 MiniMax M3 only
- Shared results
- 12
- Inkling-Small only
- 13
- MiniMax M3 only
- 15
- Like-for-like categories
- 2 / 8
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign 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.
Knowledge
Like-for-like- Inkling-Small
- 56.5
- Supported · #46/183
- MiniMax M3
- 53.2
- Supported · #64/183
- Basis
- BenchAlign lane · 6 vs 2 public rows
- Reading
- Inkling-Small leads · intervals overlap
Coding
Directional only- Inkling-Small
- 43.8
- Supported · #97/151
- MiniMax M3
- 48.8
- Estimated · #66/151
- Basis
- BenchAlign lane · 6 vs 10 public rows
- Reading
- Directional only
Multimodal
Directional only- Inkling-Small
- 48.8
- #39/48
- MiniMax M3
- 52.2
- #34/48
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Directional only
Instruction following
Directional only- Inkling-Small
- 89.6
- #25/123
- MiniMax M3
- 93.7
- #4/123
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Inkling-Small
- 42.7
- Unranked · 3 rankable rows
- MiniMax M3
- 78.0
- #4/20
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Inkling-Small
- 76.9
- Unranked · 2 rankable rows
- MiniMax M3
- Not ranked
- Basis
- Provisional lane · 2 vs 1 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Inkling-Small
- Not ranked
- MiniMax M3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Inkling-Small | MiniMax M3 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 36.9Supported · #128/152 | 42.1Supported · #107/152 | Like-for-likeBenchAlign lane · 5 vs 9 public rows | MiniMax M3 leads · intervals overlap |
| Knowledge | 56.5Supported · #46/183 | 53.2Supported · #64/183 | Like-for-likeBenchAlign lane · 6 vs 2 public rows | Inkling-Small leads · intervals overlap |
| Coding | 43.8Supported · #97/151 | 48.8Estimated · #66/151 | Directional onlyBenchAlign lane · 6 vs 10 public rows | Directional only |
| Multimodal | 48.8#39/48 | 52.2#34/48 | Directional onlyProvisional lane · 2 vs 2 weighted rows | Directional only |
| Instruction following | 89.6#25/123 | 93.7#4/123 | Directional onlyProvisional lane · 1 vs 0 weighted rows | Directional only |
| Reasoning | 42.7Unranked · 3 rankable rows | 78.0#4/20 | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Math | 76.9Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 2 vs 1 weighted rows | Not comparable |
| Multilingual | 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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
BrowseComp
Agentic
MMMU-Pro
Multimodal
LiveCodeBench (Vals)
Coding
SWE-bench Pro
Coding
MMLU-Pro (Vals)
Knowledge
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
- Inkling-Small
- $0.0013
- Fits in one request
- MiniMax M3
- $0.0009
- Fits in one request
MiniMax M3 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Inkling-Small
- $0.03332
- Fits in one request
- MiniMax M3
- $0.0186
- Fits in one request
MiniMax M3 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Inkling-Small
- $0.0492
- Fits in one request
- MiniMax M3
- $0.03
- Fits in one request
MiniMax M3 has the lower modeled cost
Costs use the listed standard API rates.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationInkling-SmallMiniMax M3
Context window
Maximum documented context; output-token limits may be lower.
Inkling-Small
1M
MiniMax M3
1M
API model ID
Inkling-Small
Not sourced
MiniMax M3
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Inkling-Small
$0.116 per 1M cached input tokens
MiniMax M3
$0.06 per 1M cached input tokens
Documented inputs
Inkling-Small
Not sourced
MiniMax M3
Not sourced
Documented outputs
Inkling-Small
Not sourced
MiniMax M3
Not sourced
Provider availability
Inkling-Small
Not sourced
MiniMax M3
Not sourced
Reasoning profile
Inkling-Small
Hybrid
MiniMax M3
Non-Reasoning
Weight access
Inkling-Small
Open Weight
MiniMax M3
Open Weight
License
Inkling-Small
Open Weight
MiniMax M3
Open Weight
Release date
Inkling-Small
2026-07-30
MiniMax M3
2026-06-01
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
- MiniMax M3 has the higher public score estimate, 61.55 versus 59.25, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.03332 vs $0.0186. Cache-heavy agent loop: $0.0492 vs $0.03.
- Context tradeoff
- Both models list 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 evidence40 rows
Agentic
Terminal-Bench 2.0
Inkling-Small64.7%SourceMiniMax M366%SourceMiniMax M3 leads this result
BrowseComp
Inkling-Small77.4%SourceMiniMax M383.5%SourceMiniMax M3 leads this result
MCP Atlas
Inkling-Small79.6%SourceMiniMax M374.2%SourceInkling-Small leads this result
Toolathlon-Verified
Inkling-Small54.4%SourceMiniMax M3—Not directly comparable
Terminal-Bench 2.1 (Vals)
Inkling-Small55.1%SourceMiniMax M353.6%SourceInkling-Small leads this result
OSWorld-Verified
Inkling-Small—MiniMax M370.1%SourceNot directly comparable
Claw-Eval
Inkling-Small—MiniMax M374.5%SourceNot directly comparable
BankerToolBench
Inkling-Small—MiniMax M376.1%SourceNot directly comparable
ResearchClawBench
Inkling-Small—MiniMax M319.8%SourceNot directly comparable
OSWorld 2.0
Inkling-Small—MiniMax M34.6%SourceNot directly comparable
Coding
SWE-bench Verified
Inkling-Small80.2%SourceMiniMax M380.5%SourceMiniMax M3 leads this result
SWE-bench Pro
Inkling-Small55.9%SourceMiniMax M359%SourceMiniMax M3 leads this result
Terminal-Bench 2.0
Inkling-Small64.7%SourceMiniMax M366.0%SourceMiniMax M3 leads this result
SciCode
Inkling-Small48.7%SourceMiniMax M3—Not directly comparable
LiveCodeBench (Vals)
Inkling-Small85.9%SourceMiniMax M382.2%SourceInkling-Small leads this result
SWE-bench (Vals)
Inkling-Small82.2%SourceMiniMax M375.0%SourceInkling-Small leads this result
NL2Repo
Inkling-Small—MiniMax M342.1%SourceNot directly comparable
VIBE V2
Inkling-Small—MiniMax M350.1%SourceNot directly comparable
SVG-Bench
Inkling-Small—MiniMax M363.7%SourceNot directly comparable
KernelBench Hard
Inkling-Small—MiniMax M328.8%SourceNot directly comparable
OpenHarmony Bench
Inkling-Small—MiniMax M348.4%SourceNot directly comparable
Reasoning
Knowledge
GPQA
Inkling-Small89.5%SourceMiniMax M3—Not directly comparable
GPQA-D
Inkling-Small89.5%SourceMiniMax M3—Not directly comparable
HLE
Inkling-Small47.8%SourceMiniMax M3—Not directly comparable
HLE w/o tools
Inkling-Small31.6%SourceMiniMax M3—Not directly comparable
GPQA Diamond (Vals)
Inkling-Small83.6%SourceMiniMax M392.7%SourceMiniMax M3 leads this result
MMLU-Pro (Vals)
Inkling-Small85.6%SourceMiniMax M384.2%SourceInkling-Small leads this result
Math
Multimodal
MMMU-Pro
Inkling-Small74%SourceMiniMax M378.1%SourceMiniMax M3 leads this result
CharXiv
Inkling-Small81.3%SourceMiniMax M3—Not directly comparable
CharXiv w/o tools
Inkling-Small77.4%SourceMiniMax M3—Not directly comparable
OfficeQA Pro
Inkling-Small—MiniMax M345.1%SourceNot directly comparable
OmniDocBench 1.5
Inkling-Small—MiniMax M391.6%SourceNot directly comparable
VideoMMMU
Inkling-Small—MiniMax M384.6%SourceNot directly comparable
Video-MME (with subtitle)
Inkling-Small—MiniMax M385.4%SourceNot directly comparable
Instruction following
IFBench
Inkling-Small82.2%SourceMiniMax M3—Not directly comparable
Frequently asked questions
Which is better, Inkling-Small or MiniMax M3?
MiniMax M3 has the higher public score estimate, 61.55 versus 59.25, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Inkling-Small or MiniMax M3?
MiniMax M3 scores higher for coding on the public lane, 48.8 to 43.8. MiniMax M3 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, Inkling-Small or MiniMax M3?
MiniMax M3 leads the public agentic tasks lane, 42.1 to 36.9, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Inkling-Small or MiniMax M3?
For the stated presets, chat costs $0.0013 on Inkling-Small and $0.0009 on MiniMax M3; repository review costs $0.03332 and $0.0186; the cache-heavy agent loop costs $0.0492 and $0.03. Costs use the listed standard API rates.
Which has the larger context window, Inkling-Small or MiniMax M3?
Both models list the same context window, 1M.
Related comparisons
Last updated September 10, 2026
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