Agentic
Like-for-like- Mistral Medium 3.5 128B
- 21.9
- Supported · #152/154
- Muse Spark 1.2
- 61.0
- Supported · #16/154
- Basis
- BenchAlign lane · 3 vs 2 public rows
- Reading
- Muse Spark 1.2 leads
Mistral Medium 3.5 128B vs Muse Spark 1.2
Decision reading
Muse Spark 1.2 has the higher public score, 70.28 versus 42.56, and the 90% score intervals do not overlap.
3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Updated September 18, 2026. Rank says Muse Spark 1.2 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
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.
Agentic work
Tool use, computer use, and multi-step task completion
Muse Spark 1.2
Muse Spark 1.2 leads on the public agentic lane, 61 to 21.9, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Long documents
Prompts that approach the documented context limit
Muse Spark 1.2
Muse Spark 1.2 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Muse Spark 1.2
Muse Spark 1.2 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
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Muse Spark 1.2
Muse Spark 1.2 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.
Confidence: rate-fallback
Repository review cost
50K fresh input + 3K output tokens
Muse Spark 1.2
Muse Spark 1.2 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
Mistral Medium 3.5 128B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
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.
39.2Mistral Medium 3.5 128B60.0Muse Spark 1.2
Directional only · BenchAlign
Muse Spark 1.2 scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
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
5 Muse Spark 1.2 only
- Shared results
- 3
- Mistral Medium 3.5 128B only
- 4
- Muse Spark 1.2 only
- 5
- Like-for-like categories
- 1 / 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.
Coding
Directional only- Mistral Medium 3.5 128B
- 39.2
- Estimated · #124/154
- Muse Spark 1.2
- 60.0
- Supported · #21/154
- Basis
- BenchAlign lane · 2 vs 5 public rows
- Reading
- Directional only
Knowledge
Directional only- Mistral Medium 3.5 128B
- 40.6
- Supported · #133/184
- Muse Spark 1.2
- 70.7
- Estimated · #10/184
- Basis
- BenchAlign lane · 2 vs 1 public rows
- Reading
- Directional only
Reasoning
Not comparable- Mistral Medium 3.5 128B
- 68.6
- Unranked · 2 rankable rows
- Muse Spark 1.2
- 75.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Mistral Medium 3.5 128B
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Mistral Medium 3.5 128B
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Mistral Medium 3.5 128B
- 55.7
- Unranked · 1 rankable row
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Mistral Medium 3.5 128B
- 82.6
- #48/124
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Mistral Medium 3.5 128B | Muse Spark 1.2 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 21.9Supported · #152/154 | 61.0Supported · #16/154 | Like-for-likeBenchAlign lane · 3 vs 2 public rows | Muse Spark 1.2 leads |
| Coding | 39.2Estimated · #124/154 | 60.0Supported · #21/154 | Directional onlyBenchAlign lane · 2 vs 5 public rows | Directional only |
| Knowledge | 40.6Supported · #133/184 | 70.7Estimated · #10/184 | Directional onlyBenchAlign lane · 2 vs 1 public rows | Directional only |
| Reasoning | 68.6Unranked · 2 rankable rows | 75.3Unranked · 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 | 55.7Unranked · 1 rankable row | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 82.6#48/124 | 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) 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.
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
Mistral Medium 3.5 128B: 75.3%Muse Spark 1.2: 88.3%Normalized gap 13.0Mistral Medium 3.5 128B source Muse Spark 1.2 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
- Mistral Medium 3.5 128B
- $0.00525
- Fits in one request
- Muse Spark 1.2
- $0.00338
- Fits in one request
Muse Spark 1.2 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
- Muse Spark 1.2
- $0.07525
- Fits in one request
Muse Spark 1.2 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
- Muse Spark 1.2
- $0.0975
- Fits in one request
Muse Spark 1.2 has the lower modeled cost
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.
SpecificationMistral Medium 3.5 128BMuse Spark 1.2
Context window
Maximum documented context; output-token limits may be lower.
Mistral Medium 3.5 128B
256K
Muse Spark 1.2
API model ID
Mistral Medium 3.5 128B
Not sourced
Muse Spark 1.2
muse-spark-1.2
Meta: Muse Spark 1.2 model pageCached-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
Muse Spark 1.2
$0.15 per 1M cached input tokens
Meta: Muse Spark 1.2 model pageDocumented inputs
Mistral Medium 3.5 128B
Not sourced
Muse Spark 1.2
Not sourced
Documented outputs
Mistral Medium 3.5 128B
Not sourced
Muse Spark 1.2
Not sourced
Provider availability
Mistral Medium 3.5 128B
Not sourced
Muse Spark 1.2
Not sourced
Reasoning profile
Mistral Medium 3.5 128B
Reasoning
Muse Spark 1.2
Reasoning
Weight access
Mistral Medium 3.5 128B
Open Weight
Muse Spark 1.2
Proprietary
License
Mistral Medium 3.5 128B
Open Weight
Muse Spark 1.2
Proprietary
Release date
Mistral Medium 3.5 128B
2026-04-29
Muse Spark 1.2
2026-08-05
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
- Muse Spark 1.2 has the higher public score, 70.28 versus 42.56, and the 90% score intervals do not overlap.
- Workload cost
- Repository review: $0.0975 vs $0.07525. Cache-heavy agent loop: $0.405 vs $0.0975.
- Context tradeoff
- Muse Spark 1.2 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 evidence12 rows
Agentic
τ³-bench results
Mistral Medium 3.5 128B91.4%SourceMuse Spark 1.2—Not directly comparable
Gert Labs
Mistral Medium 3.5 128B39.10%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.1 (Vals)
Mistral Medium 3.5 128B39.0%SourceMuse Spark 1.269.7%SourceMuse Spark 1.2 leads this result
Terminal-Bench 2.1
Mistral Medium 3.5 128B—Muse Spark 1.282.9%SourceNot directly comparable
Coding
SWE-bench Verified
Mistral Medium 3.5 128B77.6%SourceMuse Spark 1.2—Not directly comparable
SWE-bench (Vals)
Mistral Medium 3.5 128B66.4%SourceMuse Spark 1.286.6%SourceMuse Spark 1.2 leads this result
Terminal-Bench 2.1
Mistral Medium 3.5 128B—Muse Spark 1.282.9%SourceNot directly comparable
DeepSWE
Mistral Medium 3.5 128B—Muse Spark 1.259.3%SourceNot directly comparable
VulcanBench v3
Mistral Medium 3.5 128B—Muse Spark 1.287.0%SourceNot directly comparable
FrontierSWE v2
Mistral Medium 3.5 128B—Muse Spark 1.212.0%SourceNot directly comparable
Knowledge
Questions
Which is better, Mistral Medium 3.5 128B or Muse Spark 1.2?
Muse Spark 1.2 has the higher public score, 70.28 versus 42.56, 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, Mistral Medium 3.5 128B or Muse Spark 1.2?
Muse Spark 1.2 scores higher for coding on the public lane, 60 to 39.2. Mistral Medium 3.5 128B 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, Mistral Medium 3.5 128B or Muse Spark 1.2?
Muse Spark 1.2 leads the public agentic tasks lane, 61 to 21.9, with Supported evidence for both models and non-overlapping 90% intervals.
Which costs less, Mistral Medium 3.5 128B or Muse Spark 1.2?
For the stated presets, chat costs $0.00525 on Mistral Medium 3.5 128B and $0.00337 on Muse Spark 1.2; repository review costs $0.0975 and $0.07525; the cache-heavy agent loop costs $0.405 and $0.0975. 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, Mistral Medium 3.5 128B or Muse Spark 1.2?
Muse Spark 1.2 has the larger documented context window: 1M, compared with 256K.
Related comparisons
Last updated September 18, 2026
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