Coding
Directional only- Claude 3.5 Sonnet
- 49.0
- MiniMax M3
- 72.2
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Claude 3.5 Sonnet vs MiniMax M3
Updated August 30, 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, 68.73 versus 48.38, and the 90% score intervals do not overlap.
1 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
MiniMax M3
MiniMax M3 has the larger documented context window.
Confidence: documented
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
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
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
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. Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 Claude 3.5 Sonnet only
1 Shared
21 MiniMax M3 only
- Shared results
- 1
- Claude 3.5 Sonnet only
- 3
- MiniMax M3 only
- 21
- Like-for-like categories
- 0 / 8
1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
Agentic
Not comparable- Claude 3.5 Sonnet
- Not measured
- MiniMax M3
- 72.3
- Weighted basis
- 0 vs 3 rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude 3.5 Sonnet
- Not measured
- MiniMax M3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude 3.5 Sonnet
- 59.4
- MiniMax M3
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Claude 3.5 Sonnet
- 1.6
- MiniMax M3
- 85.7
- Weighted basis
- 2 vs 1 rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude 3.5 Sonnet
- Not measured
- MiniMax M3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude 3.5 Sonnet
- Not measured
- MiniMax M3
- 64.9
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude 3.5 Sonnet
- Not measured
- MiniMax M3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Claude 3.5 Sonnet | MiniMax M3 | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 49.0 | 72.2 | Directional only1 vs 2 rows | Directional only |
| Agentic | Not measured | 72.3 | Not comparable0 vs 3 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 59.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 1.6 | 85.7 | Not comparable2 vs 1 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | 64.9 | Not comparable0 vs 2 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.
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.
SWE-bench Verified
Coding
Claude 3.5 Sonnet: 49%MiniMax M3: 80.5%Normalized gap 31.5Claude 3.5 Sonnet source MiniMax M3 source
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
- Claude 3.5 Sonnet
- $0.0105
- 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
- Claude 3.5 Sonnet
- $0.195
- 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
- Claude 3.5 Sonnet
- $0.81
- Does not fit in one request
- Cached input priced at the published list-input rate
- MiniMax M3
- $0.03
- Fits in one request
Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude 3.5 SonnetMiniMax M3
Context window
Maximum documented context; output-token limits may be lower.
Claude 3.5 Sonnet
200K
MiniMax M3
1M
API model ID
Claude 3.5 Sonnet
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.
Claude 3.5 Sonnet
Not published
MiniMax M3
$0.06 per 1M cached input tokens
Documented inputs
Claude 3.5 Sonnet
Not sourced
MiniMax M3
Not sourced
Documented outputs
Claude 3.5 Sonnet
Not sourced
MiniMax M3
Not sourced
Provider availability
Claude 3.5 Sonnet
Not sourced
MiniMax M3
Not sourced
Reasoning profile
Claude 3.5 Sonnet
Non-Reasoning
MiniMax M3
Non-Reasoning
Weight access
Claude 3.5 Sonnet
Proprietary
MiniMax M3
Open Weight
License
Claude 3.5 Sonnet
Proprietary
MiniMax M3
Open Weight
Release date
Claude 3.5 Sonnet
2024-06-01
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, 68.73 versus 48.38, and the 90% score intervals do not overlap.
- Workload cost
- Repository review: $0.195 vs $0.0186. Cache-heavy agent loop: $0.81 vs $0.03.
- Context tradeoff
- MiniMax M3 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 evidence25 rows
Agentic
Terminal-Bench 2.0
Claude 3.5 Sonnet—MiniMax M366%SourceNot directly comparable
BrowseComp
Claude 3.5 Sonnet—MiniMax M383.5%SourceNot directly comparable
OSWorld-Verified
Claude 3.5 Sonnet—MiniMax M370.1%SourceNot directly comparable
MCP Atlas
Claude 3.5 Sonnet—MiniMax M374.2%SourceNot directly comparable
Claw-Eval
Claude 3.5 Sonnet—MiniMax M374.5%SourceNot directly comparable
BankerToolBench
Claude 3.5 Sonnet—MiniMax M376.1%SourceNot directly comparable
ResearchClawBench
Claude 3.5 Sonnet—MiniMax M319.8%SourceNot directly comparable
OSWorld 2.0
Claude 3.5 Sonnet—MiniMax M34.6%SourceNot directly comparable
Coding
SWE-bench Verified
Claude 3.5 Sonnet49%SourceMiniMax M380.5%SourceMiniMax M3 leads this result
SWE-bench Pro
Claude 3.5 Sonnet—MiniMax M359%SourceNot directly comparable
Terminal-Bench 2.0
Claude 3.5 Sonnet—MiniMax M366.0%SourceNot directly comparable
NL2Repo
Claude 3.5 Sonnet—MiniMax M342.1%SourceNot directly comparable
VIBE V2
Claude 3.5 Sonnet—MiniMax M350.1%SourceNot directly comparable
SVG-Bench
Claude 3.5 Sonnet—MiniMax M363.7%SourceNot directly comparable
KernelBench Hard
Claude 3.5 Sonnet—MiniMax M328.8%SourceNot directly comparable
OpenHarmony Bench
Claude 3.5 Sonnet—MiniMax M348.4%SourceNot directly comparable
Knowledge
GPQA
Claude 3.5 Sonnet59.4%SourceMiniMax M3—Not directly comparable
Math
Multimodal
OfficeQA Pro
Claude 3.5 Sonnet—MiniMax M345.1%SourceNot directly comparable
OmniDocBench 1.5
Claude 3.5 Sonnet—MiniMax M391.6%SourceNot directly comparable
MMMU-Pro
Claude 3.5 Sonnet—MiniMax M378.1%SourceNot directly comparable
VideoMMMU
Claude 3.5 Sonnet—MiniMax M384.6%SourceNot directly comparable
Video-MME (with subtitle)
Claude 3.5 Sonnet—MiniMax M385.4%SourceNot directly comparable
Frequently asked questions
Which is better, Claude 3.5 Sonnet or MiniMax M3?
MiniMax M3 has the higher public score, 68.73 versus 48.38, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, Claude 3.5 Sonnet or MiniMax M3?
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Claude 3.5 Sonnet or MiniMax M3?
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, Claude 3.5 Sonnet or MiniMax M3?
For the stated presets, chat costs $0.0105 on Claude 3.5 Sonnet and $0.0009 on MiniMax M3; repository review costs $0.195 and $0.0186; the cache-heavy agent loop costs $0.81 and $0.03. Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude 3.5 Sonnet or MiniMax M3?
MiniMax M3 has the larger documented context window: 1M, compared with 200K.
Related comparisons
Last updated August 30, 2026
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