Knowledge
Directional only- GLM-4.5-Air
- 39.8
- Estimated · #132/183
- Mistral Medium 3.5 128B
- 39.0
- Supported · #140/183
- Basis
- BenchAlign lane · 0 vs 2 public rows
- Reading
- Directional only
GLM-4.5-Air vs Mistral Medium 3.5 128B
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.
0 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.
Long documents
Prompts that approach the documented context limit
Mistral Medium 3.5 128B
Mistral Medium 3.5 128B has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
GLM-4.5-Air
GLM-4.5-Air 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
GLM-4.5-Air
GLM-4.5-Air 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
GLM-4.5-Air is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
GLM-4.5-Air is not ranked on the public lane for agentic, so no winner is named for agentic.
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. GLM-4.5-Air does not fit this workload in one request. GLM-4.5-Air has no published cached-input rate, so cached tokens use its listed input rate. Mistral Medium 3.5 128B 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.
7 Mistral Medium 3.5 128B only
- Shared results
- 0
- GLM-4.5-Air only
- 0
- Mistral Medium 3.5 128B only
- 7
- Like-for-like categories
- 0 / 8
2 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.
Instruction following
Directional only- GLM-4.5-Air
- 43.5
- #99/123
- Mistral Medium 3.5 128B
- 84.0
- #48/123
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Directional only
Agentic
Not comparable- GLM-4.5-Air
- Not ranked
- Mistral Medium 3.5 128B
- 21.9
- Supported · #150/152
- Basis
- BenchAlign lane · 0 vs 3 public rows
- Reading
- Not comparable
Coding
Not comparable- GLM-4.5-Air
- Not ranked
- Mistral Medium 3.5 128B
- 36.9
- Estimated · #127/151
- Basis
- BenchAlign lane · 0 vs 2 public rows
- Reading
- Not comparable
Reasoning
Not comparable- GLM-4.5-Air
- 53.1
- Unranked · 2 rankable rows
- Mistral Medium 3.5 128B
- 68.6
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- GLM-4.5-Air
- Not ranked
- Mistral Medium 3.5 128B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- GLM-4.5-Air
- Not ranked
- Mistral Medium 3.5 128B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- GLM-4.5-Air
- Not ranked
- Mistral Medium 3.5 128B
- 55.6
- Unranked · 1 rankable row
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | GLM-4.5-Air | Mistral Medium 3.5 128B | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 39.8Estimated · #132/183 | 39.0Supported · #140/183 | Directional onlyBenchAlign lane · 0 vs 2 public rows | Directional only |
| Instruction following | 43.5#99/123 | 84.0#48/123 | Directional onlyProvisional lane · 0 vs 0 weighted rows | Directional only |
| Agentic | Not ranked | 21.9Supported · #150/152 | Not comparableBenchAlign lane · 0 vs 3 public rows | Not comparable |
| Coding | Not ranked | 36.9Estimated · #127/151 | Not comparableBenchAlign lane · 0 vs 2 public rows | Not comparable |
| Reasoning | 53.1Unranked · 2 rankable rows | 68.6Unranked · 2 rankable rows | 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 |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 55.6Unranked · 1 rankable row | 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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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
- GLM-4.5-Air
- $0.00075
- Fits in one request
- Mistral Medium 3.5 128B
- $0.00525
- Fits in one request
GLM-4.5-Air has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- GLM-4.5-Air
- $0.0133
- Fits in one request
- Mistral Medium 3.5 128B
- $0.0975
- Fits in one request
GLM-4.5-Air has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GLM-4.5-Air
- $0.055
- Does not fit in one request
- Cached input priced at the published list-input rate
- Mistral Medium 3.5 128B
- $0.405
- Fits in one request
- Cached input priced at the published list-input rate
GLM-4.5-Air does not fit this workload in one request. GLM-4.5-Air has no published cached-input rate, so cached tokens use its listed input rate. Mistral Medium 3.5 128B 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.
SpecificationGLM-4.5-AirMistral Medium 3.5 128B
Context window
Maximum documented context; output-token limits may be lower.
GLM-4.5-Air
128K
Mistral Medium 3.5 128B
256K
API model ID
GLM-4.5-Air
Not sourced
Mistral Medium 3.5 128B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GLM-4.5-Air
Not published
Mistral Medium 3.5 128B
Not published
Documented inputs
GLM-4.5-Air
Not sourced
Mistral Medium 3.5 128B
Not sourced
Documented outputs
GLM-4.5-Air
Not sourced
Mistral Medium 3.5 128B
Not sourced
Provider availability
GLM-4.5-Air
Not sourced
Mistral Medium 3.5 128B
Not sourced
Reasoning profile
GLM-4.5-Air
Non-Reasoning
Mistral Medium 3.5 128B
Reasoning
Weight access
GLM-4.5-Air
Proprietary
Mistral Medium 3.5 128B
Open Weight
License
GLM-4.5-Air
Proprietary
Mistral Medium 3.5 128B
Open Weight
Release date
GLM-4.5-Air
2025-06-01
Mistral Medium 3.5 128B
2026-04-29
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
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- Repository review: $0.0133 vs $0.0975. Cache-heavy agent loop: $0.055 vs $0.405.
- Context tradeoff
- Mistral Medium 3.5 128B has the larger documented window (256K).
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 evidence7 rows
Agentic
Coding
Knowledge
Frequently asked questions
Which is better, GLM-4.5-Air or Mistral Medium 3.5 128B?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, GLM-4.5-Air or Mistral Medium 3.5 128B?
GLM-4.5-Air is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, GLM-4.5-Air or Mistral Medium 3.5 128B?
GLM-4.5-Air is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, GLM-4.5-Air or Mistral Medium 3.5 128B?
For the stated presets, chat costs $0.00075 on GLM-4.5-Air and $0.00525 on Mistral Medium 3.5 128B; repository review costs $0.0133 and $0.0975; the cache-heavy agent loop costs $0.055 and $0.405. GLM-4.5-Air does not fit this workload in one request. GLM-4.5-Air has no published cached-input rate, so cached tokens use its listed input rate. Mistral Medium 3.5 128B has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, GLM-4.5-Air or Mistral Medium 3.5 128B?
Mistral Medium 3.5 128B has the larger documented context window: 256K, compared with 128K.
Related comparisons
Last updated September 10, 2026
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