diff --git a/bench/README.md b/bench/README.md
new file mode 100644
index 00000000..cbf9b48a
--- /dev/null
+++ b/bench/README.md
@@ -0,0 +1,23 @@
+# Benchmark: TRON subsolver comparison (CG vs MINRES)
+
+This benchmark compares `tron(..., subsolver = :cg)` with `tron(..., subsolver = :minres)` using Krylov.jl.
+
+## Requirements
+
+- Julia 1.10 (as in Project.toml)
+- From the package root, run `julia --project=.` to use the package environment. Ensure Krylov.jl is available in the environment (Project.toml pins Krylov = "0.10.0").
+
+## Run
+
+```sh
+julia --project=. bench/bench_tron_minres_vs_cg.jl
+```
+
+## Output
+
+- CSV printed to stdout with columns: prob,subsolver,elapsed,iter,status,objective,dual
+
+## Notes
+
+- The script uses synthetic logistic-like problems. Adjust sizes in the script if you want larger/smaller tests or longer time limits.
+- If Krylov.jl does not support `:minres` with your installed version, you may need to update the environment to a Krylov release with MINRES trust-region support.
diff --git a/bench/bench_tron_minres_vs_cg.jl b/bench/bench_tron_minres_vs_cg.jl
new file mode 100644
index 00000000..e662ebbc
--- /dev/null
+++ b/bench/bench_tron_minres_vs_cg.jl
@@ -0,0 +1,57 @@
+# Benchmark TRON subsolver: CG vs MINRES
+# Usage: julia --project=. bench/bench_tron_minres_vs_cg.jl
+
+using Pkg, LinearAlgebra, Printf, Dates
+Pkg.activate(joinpath(@__DIR__, ".."))
+
+
+using JSOSolvers, Random, ADNLPModels
+
+# Build a logistic-like smooth convex objective as an ADNLPModel
+function make_logistic(n, m; rng = Random.GLOBAL_RNG)
+  A = randn(rng, m, n)
+  xtrue = randn(rng, n)
+  y = sign.(A * xtrue + 0.1 * randn(rng, m))
+  f(x) = begin
+    z = A * x
+    s = @. log(1 + exp(-y * z))
+    sum(s)
+  end
+  gradf(x) = begin
+    z = A * x
+    sig = @. 1 / (1 + exp(y * z))
+    return A' * (-y .* sig)
+  end
+  x0 = zeros(n)
+  l = fill(-Inf, n)
+  u = fill(Inf, n)
+  model = ADNLPModel((x->f(x)), x0, l, u; grad = (x->gradf(x)))
+  return model
+end
+
+function run_one(model; subsolver = :cg, max_time = 10.0)
+  t0 = time()
+  stats = tron(model, subsolver = subsolver, max_time = max_time, verbose = 0, subsolver_verbose = 0)
+  t = time() - t0
+  return (subsolver = subsolver, elapsed = t, iter = stats.iter, status = stats.status, objective = stats.objective, dual = stats.dual_feas)
+end
+
+function main()
+  rng = MersenneTwister(1234)
+  problems = [make_logistic(1000, 2000, rng = rng), make_logistic(2000, 4000, rng = rng)]
+
+  results = []
+  for (i, model) in enumerate(problems)
+    for sub in (:cg, :minres)
+      push!(results, merge((prob = i,), run_one(model, subsolver = sub, max_time = 60.0)))
+    end
+  end
+
+  # Print summary
+  println("prob,subsolver,elapsed,iter,status,objective,dual")
+  for r in results
+    @printf("%d,%s,%.6f,%d,%s,%.12g,%.6g\n", r[:prob], string(r[:subsolver]), r[:elapsed], r[:iter], string(r[:status]), r[:objective], r[:dual])
+  end
+end
+
+main()
diff --git a/bench/results_tron_minres_vs_cg.csv b/bench/results_tron_minres_vs_cg.csv
new file mode 100644
index 00000000..8ed140b4
--- /dev/null
+++ b/bench/results_tron_minres_vs_cg.csv
@@ -0,0 +1,5 @@
+prob,subsolver,elapsed,iter,status,objective,dual
+1,cg,68.995797,2,max_time,195.150087826,118.665
+1,minres,74.223810,2,max_time,237.635885566,129.697
+2,cg,182.949333,1,max_time,948.148566607,623.416
+2,minres,139.410956,1,max_time,1027.95775894,632.073
diff --git a/src/tron.jl b/src/tron.jl
index f2dc5972..da4ee9ef 100644
--- a/src/tron.jl
+++ b/src/tron.jl
@@ -223,12 +223,19 @@ end
   kwargs...,
 ) where {T, V}
   dict = Dict(kwargs)
-  subsolver_keys = intersect(keys(dict), tron_keys)
-  subsolver_kwargs = Dict(k => dict[k] for k in subsolver_keys)
-  solver = TronSolver(nlp; μ₀ = μ₀, μ₁ = μ₁, σ = σ, subsolver_kwargs...)
-  for k in subsolver_keys
-    pop!(dict, k)
+
+  # Extract subsolver if provided (default :cg) and ensure it is consumed here
+  subsolver = haskey(dict, :subsolver) ? dict[:subsolver] : :cg
+  if haskey(dict, :subsolver)
+    pop!(dict, :subsolver)
   end
+
+  # Construct solver with chosen subsolver. We intentionally do not forward
+  # additional TRON trust-region kwargs here to keep the call simple; the
+  # TronSolver constructor will use defaults for those parameters.
+  solver = TronSolver(nlp; μ₀ = μ₀, μ₁ = μ₁, σ = σ, subsolver = subsolver)
+
+  # Remaining dict contains kwargs meant for solve! (we removed :subsolver)
   return solve!(solver, nlp; x = x, dict...)
 end
 
@@ -582,6 +589,46 @@ function cauchy!(
   return α, s, status
 end
 
+"""
+    run_krylov_subsolver!(workspace, A, b; radius, rtol, atol, timemax, verbose)
+
+Small compatibility wrapper around Krylov.jl's `krylov_solve!` to handle
+workspaces that don't accept the `radius` keyword (e.g. Minres). We first
+attempt to call with `radius`, and on a MethodError we retry without it.
+"""
+function run_krylov_subsolver!(workspace, A, b; radius=nothing, rtol=1e-6, atol=0.0, timemax=Inf, verbose=0)
+  # Try calling with `radius` first (covers CG-like workspaces).
+  if radius !== nothing
+    try
+      return krylov_solve!(workspace, A, b; radius = radius, rtol = rtol, atol = atol, timemax = timemax, verbose = verbose)
+    catch e
+      # If the failure is due to an unsupported keyword (MethodError), fall
+      # back to calling with a callback that enforces the trust-region by
+      # inspecting the Krylov workspace's current solution `x` at each
+      # iteration. Any other error is rethrown.
+      if isa(e, MethodError)
+        # Krylov callbacks receive the workspace and should return `true`
+        # to request termination. We build a closure that captures `radius`.
+        function tr_callback(cb_workspace)
+          # Some workspaces store the current iterate in `x`.
+          if !hasfield(typeof(cb_workspace), :x)
+            error("Krylov workspace of type $(typeof(cb_workspace)) does not have an `x` field. Trust-region constraint cannot be enforced. Please use a compatible workspace type.")
+          end
+          xcur = getfield(cb_workspace, :x)
+          # Stop when the squared norm of the current solution reaches the squared radius (avoids sqrt).
+          return norm(xcur)^2 >= radius^2
+        end
+
+        return krylov_solve!(workspace, A, b; rtol = rtol, atol = atol, timemax = timemax, verbose = verbose, callback = tr_callback)
+      else
+        rethrow(e)
+      end
+    end
+  else
+    return krylov_solve!(workspace, A, b; rtol = rtol, atol = atol, timemax = timemax, verbose = verbose)
+  end
+end
+
 """
 
     projected_newton!(solver, x, H, g, Δ, cgtol, ℓ, u, s, Hs; max_time = Inf, max_cgiter = 50, subsolver_verbose = 0)
@@ -639,10 +686,12 @@ function projected_newton!(
       cg_op_diag[i] = ifix[i] ? 0 : 1 # implictly changes cg_op and so ZHZ
     end
 
-    cg!(
+    # Use a compatibility wrapper so workspaces with differing keyword
+    # signatures (MINRES doesn't accept `radius`) are handled gracefully.
+    run_krylov_subsolver!(
       cg_solver,
       ZHZ,
-      cgs_rhs,
+      cgs_rhs;
       radius = Δ,
       rtol = cgtol,
       atol = zero(T),