Long documents
Prompts that approach the documented context limit
Qwen3.5 Flash
Qwen3.5 Flash has the larger documented context window.
Confidence: documented
Mistral Medium 3.5 128B vs Qwen3.5 Flash
Updated November 11, 2026. Rank says Qwen3.5 Flash is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
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Decision reading
Qwen3.5 Flash has the higher public point estimate, 42.31 versus 29.7. Their conditional score ranges overlap. These ranges do not establish rank confidence. 3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Model A
Mistral
29.7/100
Estimated · Public rank #179
Conditional range 15.3–44.0
- API price per 1M tokens
Mistral Medium 3.5 128B: $1.50 input / $7.50 output
Qwen3.5 Flash: $0.10 input / $0.40 output
- Context window
Mistral Medium 3.5 128B: 256K
Qwen3.5 Flash: 1M
- Released
Mistral Medium 3.5 128B: April 29, 2026
Qwen3.5 Flash: March 4, 2026
- Shared results
- 3
- Mistral Medium 3.5 128B only
- 4
- Qwen3.5 Flash only
- 2
- Like-for-like categories
- 0 / 8
Estimated: Mistral Medium 3.5 128B and Qwen3.5 Flash. 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.
Chat turn cost
1K fresh input + 500 output tokens
Qwen3.5 Flash
Qwen3.5 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Qwen3.5 Flash
Qwen3.5 Flash has the lower estimated token cost for this stated workload. Mistral Medium 3.5 128B has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 Flash 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
Qwen3.5 Flash
Qwen3.5 Flash 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
Mistral Medium 3.5 128B and Qwen3.5 Flash are 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
Qwen3.5 Flash is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
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.
21.6Mistral Medium 3.5 128B28.4Qwen3.5 Flash
Directional only · BenchAlign v5.8
Qwen3.5 Flash 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
Or describe your own job
The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.
Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.
We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
4 Mistral Medium 3.5 128B only
3 Shared
2 Qwen3.5 Flash 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.
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.
MMLU-Pro (Vals)Knowledge
Normalized gap 8.8Mistral Medium 3.5 128B:75.3%Qwen3.5 Flash:84.1%
Bars run 0–100 on each benchmark’s normalized display scale
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, reasoning, multimodal, 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.
Coding
Directional only- Mistral Medium 3.5 128B
- 21.6
- Estimated · #134/158
- Qwen3.5 Flash
- 28.4
- Estimated · #113/158
- Basis
- BenchAlign v5.8 lane · 2 vs 2 public rows
- Reading
- Directional only
Knowledge
Directional only- Mistral Medium 3.5 128B
- 28.6
- Supported · #160/179
- Qwen3.5 Flash
- 43.7
- Estimated · #101/179
- Basis
- BenchAlign v5.8 lane · 2 vs 2 public rows
- Reading
- Directional only
Agentic
Not comparable- Mistral Medium 3.5 128B
- 21.3
- Supported · #115/132
- Qwen3.5 Flash
- Not ranked
- Basis
- BenchAlign v5.8 lane · 3 vs 0 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Mistral Medium 3.5 128B
- 23.8
- Estimated · #141/158
- Qwen3.5 Flash
- Not ranked
- Basis
- BenchAlign v5.8 lane · 0 vs 0 public rows
- Reading
- Not comparable
Multimodal
Not comparable- Mistral Medium 3.5 128B
- Not ranked
- Qwen3.5 Flash
- Not ranked
- Basis
- BenchAlign v5.8 lane · 0 vs 0 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Mistral Medium 3.5 128B
- Not ranked
- Qwen3.5 Flash
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Mistral Medium 3.5 128B
- 84.0
- #55/157
- Qwen3.5 Flash
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Mistral Medium 3.5 128B
- Not ranked
- Qwen3.5 Flash
- 32.6
- Unranked · 1 rankable row
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | Mistral Medium 3.5 128B | Qwen3.5 Flash | Basis | Reading |
|---|---|---|---|---|
| Coding | 21.6Estimated · #134/158 | 28.4Estimated · #113/158 | Directional onlyBenchAlign v5.8 lane · 2 vs 2 public rows | Directional only |
| Knowledge | 28.6Supported · #160/179 | 43.7Estimated · #101/179 | Directional onlyBenchAlign v5.8 lane · 2 vs 2 public rows | Directional only |
| Agentic | 21.3Supported · #115/132 | Not ranked | Not comparableBenchAlign v5.8 lane · 3 vs 0 public rows | Not comparable |
| Reasoning | 23.8Estimated · #141/158 | Not ranked | Not comparableBenchAlign v5.8 lane · 0 vs 0 public rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 0 vs 0 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 84.0#55/157 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 32.6Unranked · 1 rankable row | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, 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 Medium 3.5 128B
- $0.00525
- Fits in one request
- Qwen3.5 Flash
- $0.0003
- Fits in one request
Qwen3.5 Flash has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Mistral Medium 3.5 128B
- $0.0975
- Fits in one request
- Qwen3.5 Flash
- $0.0062
- Fits in one request
Qwen3.5 Flash has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Mistral Medium 3.5 128B
- $0.405
- Fits in one request
- Cached input priced at the published list-input rate
- Qwen3.5 Flash
- $0.026
- Fits in one request
- Cached input priced at the published list-input rate
Qwen3.5 Flash has the lower modeled cost
Mistral Medium 3.5 128B has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 Flash has no published cached-input rate, so cached tokens use its listed input rate.
Your workload
Enter a month of tokens to price it at both models’ listed API rates.
- Mistral Medium 3.5 128B
- $30.00
- per month
- Qwen3.5 Flash
- $1.80
- per month
Standard listed rates, no batch or volume discounts.
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 Medium 3.5 128BQwen3.5 Flash
Context window
Maximum documented context; output-token limits may be lower.
Mistral Medium 3.5 128B
256K
Qwen3.5 Flash
1M
API model ID
Mistral Medium 3.5 128B
Not sourced
Qwen3.5 Flash
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Mistral Medium 3.5 128B
Not published
Qwen3.5 Flash
Not published
Documented inputs
Mistral Medium 3.5 128B
text, image
Mistral-Medium-3.5-128B model cardQwen3.5 Flash
text, image, video
Qwen Cloud model page for qwen3.5-flashDocumented outputs
Mistral Medium 3.5 128B
Qwen3.5 Flash
Provider availability
Mistral Medium 3.5 128B
Not sourced
Qwen3.5 Flash
Not sourced
Reasoning profile
Mistral Medium 3.5 128B
Reasoning
Qwen3.5 Flash
Reasoning
Weight access
Mistral Medium 3.5 128B
Open Weight
Qwen3.5 Flash
Proprietary
License
Mistral Medium 3.5 128B
Open Weight
Qwen3.5 Flash
Proprietary
Release date
Mistral Medium 3.5 128B
2026-04-29
Qwen3.5 Flash
2026-03-04
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
- Qwen3.5 Flash has the higher public point estimate, 42.31 versus 29.7. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- Repository review: $0.0975 vs $0.0062. Cache-heavy agent loop: $0.405 vs $0.026.
- Context tradeoff
- Qwen3.5 Flash has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Mistral Medium 3.5 128B or Qwen3.5 Flash?
Qwen3.5 Flash has the higher public point estimate, 42.31 versus 29.7. 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 Medium 3.5 128B or Qwen3.5 Flash?
Qwen3.5 Flash scores higher for coding on the public lane, 28.4 to 21.6. Mistral Medium 3.5 128B and Qwen3.5 Flash are 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, Mistral Medium 3.5 128B or Qwen3.5 Flash?
Qwen3.5 Flash is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Mistral Medium 3.5 128B or Qwen3.5 Flash?
For the stated presets, chat costs $0.00525 on Mistral Medium 3.5 128B and $0.0003 on Qwen3.5 Flash; repository review costs $0.0975 and $0.0062; the cache-heavy agent loop costs $0.405 and $0.026. Mistral Medium 3.5 128B has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 Flash has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Mistral Medium 3.5 128B or Qwen3.5 Flash?
Qwen3.5 Flash has the larger documented context window: 1M, compared with 256K.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Mistral Medium 3.5 128B
API / mo$6,750
Self-host / mo$6,990
Break-even52M/day
Qwen3.5 Flash
API / mo$375
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 evidence9 rows
Agentic
Coding
Knowledge
Math
FrontierMath v2 (Tiers 1-3)
Mistral Medium 3.5 128B—Qwen3.5 Flash18.246%SourceNot directly comparable
9 public results · 3 shared
Watch Mistral Medium 3.5 128B vs Qwen3.5 Flash
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Last updated November 11, 2026