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
MiniMax M3 vs Quasar 438B
Updated October 17, 2026. Rank says MiniMax M3 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Share or export
Decision reading
MiniMax M3 has the higher public point estimate, 54.9 versus 48.46. Their conditional score ranges overlap. These ranges do not establish rank confidence. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Model B
Multiverse Computing
48.46/100
Estimated · Public rank #102
Conditional range 34.1–62.8
- Shared results
- 2
- MiniMax M3 only
- 26
- Quasar 438B only
- 0
- Like-for-like categories
- 0 / 8
Supported: MiniMax M3 · Estimated: Quasar 438B. 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.
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. Quasar 438B has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
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-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Quasar 438B 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
Quasar 438B is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limitedLong documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
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.
36.4MiniMax M341.2Quasar 438B
Directional only · BenchAlign v5.8
Quasar 438B 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.
26 MiniMax M3 only
2 Shared
3 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- MiniMax M3
- 39.3
- Supported · #68/128
- Quasar 438B
- 40.0
- Estimated · #67/128
- Basis
- BenchAlign v5.8 lane · 10 vs 1 public rows
- Reading
- Directional only
Coding
Directional only- MiniMax M3
- 36.4
- Supported · #74/150
- Quasar 438B
- 41.2
- Estimated · #63/150
- Basis
- BenchAlign v5.8 lane · 10 vs 1 public rows
- Reading
- Directional only
Knowledge
Directional only- MiniMax M3
- 49.6
- Supported · #82/184
- Quasar 438B
- 46.7
- Estimated · #92/184
- Basis
- BenchAlign v5.8 lane · 2 vs 0 public rows
- Reading
- Directional only
Reasoning
Not comparable- MiniMax M3
- 82.9
- #5/28
- Quasar 438B
- 78.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- MiniMax M3
- 61.5
- #43/54
- Quasar 438B
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- MiniMax M3
- Not ranked
- Quasar 438B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- MiniMax M3
- 93.8
- #5/148
- Quasar 438B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- MiniMax M3
- Not ranked
- Quasar 438B
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
| Category | MiniMax M3 | Quasar 438B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 39.3Supported · #68/128 | 40.0Estimated · #67/128 | Directional onlyBenchAlign v5.8 lane · 10 vs 1 public rows | Directional only |
| Coding | 36.4Supported · #74/150 | 41.2Estimated · #63/150 | Directional onlyBenchAlign v5.8 lane · 10 vs 1 public rows | Directional only |
| Knowledge | 49.6Supported · #82/184 | 46.7Estimated · #92/184 | Directional onlyBenchAlign v5.8 lane · 2 vs 0 public rows | Directional only |
| Reasoning | 82.9#5/28 | 78.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 61.5#43/54 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 93.8#5/148 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 1 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
- MiniMax M3
- $0.0009
- Fits in one request
- Quasar 438B
- $0.0015
- 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
- MiniMax M3
- $0.0186
- Fits in one request
- Quasar 438B
- $0.0354
- 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
- MiniMax M3
- $0.03
- Fits in one request
- Quasar 438B
- $0.15
- Fits in one request
- Cached input priced at the published list-input rate
MiniMax M3 has the lower modeled cost
Quasar 438B 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.
SpecificationMiniMax M3Quasar 438B
Context window
Maximum documented context; output-token limits may be lower.
MiniMax M3
1M
Quasar 438B
API model ID
MiniMax M3
Not sourced
Quasar 438B
quasar-438b
CompactifAI Quasar 438B documentationCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
MiniMax M3
$0.06 per 1M cached input tokens
Quasar 438B
Not published
CompactifAI API pricingDocumented inputs
MiniMax M3
Not sourced
Quasar 438B
Not sourced
Documented outputs
MiniMax M3
Not sourced
Quasar 438B
Not sourced
Provider availability
MiniMax M3
Not sourced
Quasar 438B
Generally Available · CompactifAI API
CompactifAI Quasar 438B documentationReasoning profile
MiniMax M3
Non-Reasoning
Quasar 438B
Reasoning
Weight access
MiniMax M3
Open Weight
Quasar 438B
Proprietary
License
MiniMax M3
Open Weight
Quasar 438B
Proprietary
Release date
MiniMax M3
2026-06-01
Quasar 438B
2026-09-02
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 point estimate, 54.9 versus 48.46. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- Repository review: $0.0186 vs $0.0354. Cache-heavy agent loop: $0.03 vs $0.15.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, MiniMax M3 or Quasar 438B?
MiniMax M3 has the higher public point estimate, 54.9 versus 48.46. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, MiniMax M3 or Quasar 438B?
Quasar 438B scores higher for coding on the public lane, 41.2 to 36.4. Quasar 438B 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, MiniMax M3 or Quasar 438B?
Quasar 438B scores higher for agentic tasks on the public lane, 40 to 39.3. Quasar 438B is 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, MiniMax M3 or Quasar 438B?
For the stated presets, chat costs $0.0009 on MiniMax M3 and $0.0015 on Quasar 438B; repository review costs $0.0186 and $0.0354; the cache-heavy agent loop costs $0.03 and $0.15. Quasar 438B has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, MiniMax M3 or Quasar 438B?
Both models list the same context window, 1M.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
MiniMax M3
API / mo$1,125
Self-host / mo$13,981
Break-even818M/day
Quasar 438B
API / mo$1,800
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence28 rows
Agentic
Terminal-Bench 2.1
MiniMax M366.0%SourceQuasar 438B69.3%SourceQuasar 438B leads this result
BrowseComp
MiniMax M383.5%SourceQuasar 438B—Not directly comparable
OSWorld-Verified
MiniMax M370.1%SourceQuasar 438B—Not directly comparable
MCP Atlas
MiniMax M374.2%SourceQuasar 438B—Not directly comparable
Claw-Eval
MiniMax M374.5%SourceQuasar 438B—Not directly comparable
BankerToolBench
MiniMax M376.1%SourceQuasar 438B—Not directly comparable
ResearchClawBench
MiniMax M319.8%SourceQuasar 438B—Not directly comparable
OSWorld 2.0
MiniMax M34.6%SourceQuasar 438B—Not directly comparable
Terminal-Bench 2.1 (Vals)
MiniMax M353.6%SourceQuasar 438B—Not directly comparable
MazeBench
MiniMax M30%SourceQuasar 438B—Not directly comparable
Coding
SWE-bench Verified
MiniMax M380.5%SourceQuasar 438B—Not directly comparable
SWE-bench Pro
MiniMax M359%SourceQuasar 438B—Not directly comparable
Terminal-Bench 2.1
MiniMax M366.0%SourceQuasar 438B69.3%SourceQuasar 438B leads this result
NL2Repo
MiniMax M342.1%SourceQuasar 438B—Not directly comparable
VIBE V2
MiniMax M350.1%SourceQuasar 438B—Not directly comparable
SVG-Bench
MiniMax M363.7%SourceQuasar 438B—Not directly comparable
KernelBench Hard
MiniMax M328.8%SourceQuasar 438B—Not directly comparable
OpenHarmony Bench
MiniMax M348.4%SourceQuasar 438B—Not directly comparable
LiveCodeBench (Vals)
MiniMax M382.2%SourceQuasar 438B—Not directly comparable
SWE-bench (Vals)
MiniMax M375.0%SourceQuasar 438B—Not directly comparable
Multimodal
OfficeQA Pro
MiniMax M345.1%SourceQuasar 438B—Not directly comparable
OmniDocBench 1.5
MiniMax M391.6%SourceQuasar 438B—Not directly comparable
MMMU-Pro
MiniMax M378.1%SourceQuasar 438B—Not directly comparable
VideoMMMU
MiniMax M384.6%SourceQuasar 438B—Not directly comparable
Video-MME (with subtitle)
MiniMax M385.4%SourceQuasar 438B—Not directly comparable
Knowledge
Math
USAMO 2026
MiniMax M385.7%SourceQuasar 438B—Not directly comparable
28 public results · 2 shared
Watch MiniMax M3 vs Quasar 438B
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 5,600+ readers.
Last updated October 17, 2026