Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Mistral Large 4 and Qwen3 Max are not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Mistral Large 4 vs Qwen3 Max
Updated October 6, 2026. Rank says Mistral Large 4 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
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Decision reading
Mistral Large 4 has the higher public point estimate, 53.69 versus 40.11. Their conditional score ranges overlap. These ranges do not establish rank confidence. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 1
- Mistral Large 4 only
- 2
- Qwen3 Max only
- 1
- Like-for-like categories
- 0 / 8
Estimated: Mistral Large 4 and Qwen3 Max. 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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Mistral Large 4 and Qwen3 Max are not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documentedChat 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.
—Mistral Large 4—Qwen3 Max
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
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.
2 Mistral Large 4 only
1 Shared
1 Qwen3 Max 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.
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.
Knowledge
Directional only- Mistral Large 4
- 55.1
- Supported · #51/173
- Qwen3 Max
- 39.0
- Estimated · #105/173
- Basis
- BenchAlign v5.8 lane · 0 vs 0 public rows
- Reading
- Directional only
Agentic
Not comparable- Mistral Large 4
- Not ranked
- Qwen3 Max
- Not ranked
- Basis
- BenchAlign v5.8 lane · 2 vs 1 public rows
- Reading
- Not comparable
Coding
Not comparable- Mistral Large 4
- Not ranked
- Qwen3 Max
- Not ranked
- Basis
- BenchAlign v5.8 lane · 1 vs 1 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Mistral Large 4
- 78.2
- Unranked · 2 rankable rows
- Qwen3 Max
- 56.6
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Mistral Large 4
- 73.6
- Unranked · 1 rankable row
- Qwen3 Max
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Mistral Large 4
- Not ranked
- Qwen3 Max
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Mistral Large 4
- Not ranked
- Qwen3 Max
- 50.3
- #81/125
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Mistral Large 4
- Not ranked
- Qwen3 Max
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Mistral Large 4 | Qwen3 Max | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 55.1Supported · #51/173 | 39.0Estimated · #105/173 | Directional onlyBenchAlign v5.8 lane · 0 vs 0 public rows | Directional only |
| Agentic | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 2 vs 1 public rows | Not comparable |
| Coding | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 1 vs 1 public rows | Not comparable |
| Reasoning | 78.2Unranked · 2 rankable rows | 56.6Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 73.6Unranked · 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 |
| Instruction following | Not ranked | 50.3#81/125 | Not comparableProvisional lane · 0 vs 0 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
- Mistral Large 4
- $0.00172
- Fits in one request
- Qwen3 Max
- API rate not published
- Fits in one request
Qwen3 Max has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Mistral Large 4
- $0.04027
- Fits in one request
- Qwen3 Max
- API rate not published
- Fits in one request
Qwen3 Max has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Mistral Large 4
- $0.0485
- Fits in one request
- Qwen3 Max
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Qwen3 Max 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.
SpecificationMistral Large 4Qwen3 Max
Context window
Maximum documented context; output-token limits may be lower.
Mistral Large 4
Qwen3 Max
1M
API model ID
Mistral Large 4
Not sourced
Qwen3 Max
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Mistral Large 4
$0.07 per 1M cached input tokens
Mistral AI Mistral Large 4 model documentationQwen3 Max
No comparable hosted API rate
Documented inputs
Mistral Large 4
Not sourced
Qwen3 Max
Not sourced
Documented outputs
Mistral Large 4
Not sourced
Qwen3 Max
Not sourced
Provider availability
Mistral Large 4
Not sourced
Qwen3 Max
Not sourced
Reasoning profile
Mistral Large 4
Hybrid
Qwen3 Max
Reasoning
Weight access
Mistral Large 4
Pending
Qwen3 Max
Proprietary
License
Mistral Large 4
Pending
Qwen3 Max
Proprietary
Release date
Mistral Large 4
2026-10-06
Qwen3 Max
2026-04-20
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
- Mistral Large 4 has the higher public point estimate, 53.69 versus 40.11. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Mistral Large 4 or Qwen3 Max?
Mistral Large 4 has the higher public point estimate, 53.69 versus 40.11. 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, Mistral Large 4 or Qwen3 Max?
Mistral Large 4 and Qwen3 Max are not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Mistral Large 4 or Qwen3 Max?
Mistral Large 4 and Qwen3 Max are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Mistral Large 4 or Qwen3 Max?
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, Mistral Large 4 or Qwen3 Max?
Both models list the same context window, 1M.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence4 rows
Agentic
Coding
Vibe Code Bench
Shared sourceMistral Large 478.40%Qwen3 Max3.51%Mistral Large 4 leads this result
4 public results · 1 shared
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Last updated October 6, 2026